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Deniz GUNDUZ

Ricercatore t.d. art. 24 c. 3 lett. B presso: Dipartimento di Ingegneria "Enzo Ferrari"


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Pubblicazioni

2020 - Cache-Aided Combination Networks with Interference [Articolo su rivista]
Elkordy, A.; Motahari, A.; Nafie, M.; Gunduz, D.
abstract

Centralized coded caching and delivery is studied for a radio access combination network (RACN), whereby a set of H edge nodes (ENs), connected to a cloud server via orthogonal fronthaul links with limited capacity, serve a total of K user equipments (UEs) over wireless links. The cloud server is assumed to hold a library of N files, each of size F bits; and each user, equipped with a cache of size μ R N F bits, is connected to a distinct set of r ENs each of which equipped with a cache of size μTNF bits, where μT , μ R in [{0,1}] are the fractional cache capacities of the UEs and the ENs, respectively. The objective is to minimize the normalized delivery time (NDT), which refers to the worst case delivery latency when each user requests a single distinct file from the library. Three coded caching and transmission schemes are considered, namely the MDS-IA, soft-transfer and zero-forcing (ZF) schemes. MDS-IA utilizes maximum distance separable (MDS) codes in the placement phase and real interference alignment (IA) in the delivery phase. The achievable NDT for this scheme is presented for r=2 and arbitrary fractional cache sizes μ T and μ R , and also for arbitrary value of r and fractional cache size μT when the cache capacity of the UE is above a certain threshold. The soft-transfer scheme utilizes soft-transfer of coded symbols to ENs that implement ZF over the edge links. The achievable NDT for this scheme is presented for arbitrary r and arbitrary fractional cache sizes μT and μ R. The last scheme utilizes ZF between the ENs and the UEs without the participation of the cloud server in the delivery phase. The achievable NDT for this scheme is presented for an arbitrary value of r when the total cache size at a pair of UE and EN is sufficient to store the whole library, i.e., μT+μRgeq 1. The results indicate that the fronthaul capacity determines which scheme achieves a better performance in terms of the NDT, and the soft-transfer scheme becomes favorable as the fronthaul capacity increases.


2020 - Centralized Caching and Delivery of Correlated Contents over Gaussian Broadcast Channels [Articolo su rivista]
Yang, Q.; Hassanzadeh, P.; Gunduz, D.; Erkip, E.
abstract

Content delivery in a multi-user cache-aided broadcast network is studied, where a server holding a database of correlated contents communicates with the users over a Gaussian broadcast channel (BC). The minimum transmission power required to satisfy all possible demand combinations is studied, when the users are equipped with caches of equal size. Two centralized caching schemes are proposed, both of which not only utilize the user's local caches, but also exploit the correlation among the contents in the database. The first scheme implements uncoded cache placement and delivers coded contents to users using superposition coding. The second scheme, which is proposed for small cache sizes, places coded contents in users' caches and jointly encodes the cached contents of users and the messages targeted at them. The performance of the proposed schemes, which provide upper bounds on the required transmit power for a given cache capacity, is characterized. The scheme based on coded placement improves upon the first one for small cache sizes, and under certain conditions meets the uncoded placement lower bound. A lower bound on the required transmit power is also presented assuming uncoded cache placement. Our results indicate that exploiting the correlations among the contents in a cache-aided Gaussian BC can provide significant energy savings.


2020 - Deep Learning for Massive MIMO Channel State Acquisition and Feedback [Articolo su rivista]
Boloursaz Mashhadi, M.; Gunduz, D.
abstract

Massive multiple-input multiple-output (MIMO) systems are a main enabler of the excessive throughput requirements in 5G and future generation wireless networks as they can serve many users simultaneously with high spectral and energy efficiency. To achieve this massive MIMO systems require accurate and timely channel state information (CSI), which is acquired by a training process that involves pilot transmission, CSI estimation, and feedback. This training process incurs a training overhead, which scales with the number of antennas, users, and subcarriers. Reducing the training overhead in massive MIMO systems has been a major topic of research since the emergence of the concept. Recently, deep learning (DL)-based approaches have been proposed and shown to provide significant reduction in the CSI acquisition and feedback overhead in massive MIMO systems compared to traditional techniques. In this paper, we present an overview of the state-of-the-art DL architectures and algorithms used for CSI acquisition and feedback, and provide further research directions.


2020 - Distributed Deep Reinforcement Learning for Functional Split Control in Energy Harvesting Virtualized Small Cells [Articolo su rivista]
Temesgene, D. A.; Miozzo, M.; Gunduz, D.; Dini, P.
abstract

To meet the growing quest for enhanced network capacity, mobile network operators (MNOs) are deploying dense infrastructures of small cells. This, in turn, increases the power consumption of mobile networks, thus impacting the environment. As a result, we have seen a recent trend of powering mobile networks with harvested ambient energy to achieve both environmental and cost benefits. In this paper, we consider a network of virtualized small cells (vSCs) powered by energy harvesters and equipped with rechargeable batteries, which can opportunistically offload baseband (BB) functions to a grid-connected edge server depending on their energy availability. We formulate the corresponding grid energy and traffic drop rate minimization problem, and propose a distributed deep reinforcement learning (DDRL) solution. Coordination among vSCs is enabled via the exchange of battery state information. The evaluation of the network performance in terms of grid energy consumption and traffic drop rate confirms that enabling coordination among the vSCs via knowledge exchange achieves a performance close to the optimal. Numerical results also confirm that the proposed DDRL solution provides higher network performance, better adaptation to the changing environment, and higher cost savings with respect to a tabular multi-agent reinforcement learning (MRL) solution used as a benchmark.


2020 - Distributed Hypothesis Testing over Discrete Memoryless Channels [Articolo su rivista]
Sreekumar, S.; Gunduz, D.
abstract

A distributed binary hypothesis testing (HT) problem involving two parties, one referred to as the observer and the other as the detector is studied. The observer observes a discrete memoryless source (DMS) and communicates its observations to the detector over a discrete memoryless channel (DMC). The detector observes another DMS correlated with that at the observer, and performs a binary hypothesis test on the joint distribution of the two DMS's using its own observed data and the information received from the observer. The trade-off between the type I error probability and the type II error-exponent of the HT is explored. Single-letter lower bounds on the optimal type II error-exponent are obtained by using two different coding schemes, a separate HT and channel coding scheme and a joint HT and channel coding scheme based on hybrid coding for the matched bandwidth case. Exact single-letter characterization of the same is established for the special case of testing against conditional independence, and it is shown to be achieved by the separate HT and channel coding scheme. An example is provided where the joint scheme achieves a strictly better performance than the separation based scheme.


2020 - Energy-Aware Analog Aggregation for Federated Learning with Redundant Data [Relazione in Atti di Convegno]
Sun, Y.; Zhou, S.; Gunduz, D.
abstract

Federated learning (FL) enables workers to learn a model collaboratively by using their local data, with the help of a parameter server (PS) for global model aggregation. The high communication cost for periodic model updates and the nonindependent and identically distributed (i.i.d.) data become major bottlenecks for FL. In this work, we consider analog aggregation to scale down the communication cost with respect to the number of workers, and introduce data redundancy to the system to deal with non-i.i.d. data. We propose an online energy-aware dynamic worker scheduling policy, which maximizes the average number of workers scheduled for gradient update at each iteration under a long-term energy constraint, and analyze its performance based on Lyapunov optimization. Experiments using MNIST dataset show that, for non-i.i.d. data, doubling data storage can improve the accuracy by 9.8 under a stringent energy budget, while the proposed policy can achieve close-to-optimal accuracy without violating the energy constraint.


2020 - Federated Learning over Wireless Fading Channels [Articolo su rivista]
Amiri, M. M.; Gunduz, D.
abstract

We study federated machine learning at the wireless network edge, where limited power wireless devices, each with its own dataset, build a joint model with the help of a remote parameter server (PS). We consider a bandwidth-limited fading multiple access channel (MAC) from the wireless devices to the PS, and propose various techniques to implement distributed stochastic gradient descent (DSGD) over this shared noisy wireless channel. We first propose a digital DSGD (D-DSGD) scheme, in which one device is selected opportunistically for transmission at each iteration based on the channel conditions; the scheduled device quantizes its gradient estimate to a finite number of bits imposed by the channel condition, and transmits these bits to the PS in a reliable manner. Next, motivated by the additive nature of the wireless MAC, we propose a novel analog communication scheme, referred to as the compressed analog DSGD (CA-DSGD), where the devices first sparsify their gradient estimates while accumulating error from previous iterations, and project the resultant sparse vector into a low-dimensional vector for bandwidth reduction. We also design a power allocation scheme to align the received gradient vectors at the PS in an efficient manner. Numerical results show that D-DSGD outperforms other digital approaches in the literature; however, in general the proposed CA-DSGD algorithm converges faster than the D-DSGD scheme, and reaches a higher level of accuracy. We have observed that the gap between the analog and digital schemes increases when the datasets of devices are not independent and identically distributed (i.i.d.). Furthermore, the performance of the CA-DSGD scheme is shown to be robust against imperfect channel state information (CSI) at the devices. Overall these results show clear advantages for the proposed analog over-the-air DSGD scheme, which suggests that learning and communication algorithms should be designed jointly to achieve the best end-to-end performance in machine learning applications at the wireless edge.


2020 - Information Transmission Bounds between Moving Terminals [Articolo su rivista]
Faqir, O. J.; Kerrigan, E. C.; Gunduz, D.
abstract

In networks of mobile autonomous agents, e.g. for data acquisition, we may wish to maximize data transfer or to reliably transfer a minimum amount of data, subject to quality of service or energy constraints. These requirements can be guaranteed through both offline node design/specifications and online trajectory/communications design. Regardless of the distance between them, for a stationary point-to-point transmitter-receiver pair communicating across a single link under average power constraints, the total data transfer is unbounded as time tends to infinity. In contrast, we show that if the transmitter/receiver is moving at any constant speed away from each other, then the maximum transmittable data is bounded. Although general closed-form expressions as a function of communication and mobility profile parameters do not yet exist, we provide closed-form expressions for particular cases, such as ideal free space path loss. Under more general scenarios we instead give lower bounds on the total transmittable information across a single link between mobile nodes.


2020 - Machine Learning at the Wireless Edge: Distributed Stochastic Gradient Descent Over-the-Air [Articolo su rivista]
Mohammadi Amiri, M.; Gunduz, D.
abstract

We study federated machine learning (ML) at the wireless edge, where power- and bandwidth-limited wireless devices with local datasets carry out distributed stochastic gradient descent (DSGD) with the help of a parameter server (PS). Standard approaches assume separate computation and communication, where local gradient estimates are compressed and transmitted to the PS over orthogonal links. Following this digital approach, we introduce D-DSGD, in which the wireless devices employ gradient quantization and error accumulation, and transmit their gradient estimates to the PS over a multiple access channel (MAC). We then introduce a novel analog scheme, called A-DSGD, which exploits the additive nature of the wireless MAC for over-the-air gradient computation, and provide convergence analysis for this approach. In A-DSGD, the devices first sparsify their gradient estimates, and then project them to a lower dimensional space imposed by the available channel bandwidth. These projections are sent directly over the MAC without employing any digital code. Numerical results show that A-DSGD converges faster than D-DSGD thanks to its more efficient use of the limited bandwidth and the natural alignment of the gradient estimates over the channel. The improvement is particularly compelling at low power and low bandwidth regimes. We also illustrate for a classification problem that, A-DSGD is more robust to bias in data distribution across devices, while D-DSGD significantly outperforms other digital schemes in the literature. We also observe that both D-DSGD and A-DSGD perform better with the number of devices, showing their ability in harnessing the computation power of edge devices.


2020 - Management and Orchestration of Virtual Network Functions via Deep Reinforcement Learning [Articolo su rivista]
Pujol Roig, J. S.; Gutierrez-Estevez, D.; Gunduz, D.
abstract

Management and orchestration (MANO) of resources by virtual network functions (VNFs) represents one of the key challenges towards a fully virtualized network architecture as envisaged by 5G standards. Current threshold-based policies inefficiently over-provision network resources and under-utilize available hardware, incurring high cost for network operators, and consequently, the users. In this work, we present a MANO algorithm for VNFs allowing a central unit (CU) to learn to autonomously re-configure resources (processing power and storage), deploy new VNF instances, or offload them to the cloud, depending on the network conditions, available pool of resources, and the VNF requirements, with the goal of minimizing a cost function that takes into account the economical cost as well as latency and the quality-of-service (QoS) experienced by the users. First, we formulate the stochastic resource optimization problem as a parameterized action Markov decision process (PAMDP). Then, we propose a solution based on deep reinforcement learning (DRL). More precisely, we present a novel RL approach, called parameterized action twin (PAT) deterministic policy gradient, which leverages an actor-critic architecture to learn to provision resources to the VNFs in an online manner. Finally, we present numerical performance results, and map them to 5G key performance indicators (KPIs). To the best of our knowledge, this is the first work that considers DRL for MANO of VNFs' physical resources.


2020 - Mobility-Aware Coded Storage and Delivery [Articolo su rivista]
Ozfatura, E.; Gunduz, D.
abstract

We consider a cache-enabled heterogeneous cellular network, where mobile users (MUs) connect to multiple cache-enabled small-cell base stations (SBSs) during a video downloading session. SBSs can deliver these requests using their local cache contents as well as by downloading them from a macro-cell base station (MBS), which has access to the file library. We introduce a novel mobility-aware content storage and delivery scheme, which jointly exploits coded storage at the SBSs and coded delivery from the MBS to reduce the backhaul load from the MBS to the SBSs. We show that the proposed scheme provides a significant reduction both in the backhaul load when the cache capacity is sufficiently large, and in the number of sub-files required. Overall, for practical scenarios, in which the number of sub-files that can be created is limited either by the size of the files, or by the protocol overhead, the proposed coded caching and delivery scheme decidedly outperforms state-of-the-art alternatives. Finally, we show that the benefits of the proposed scheme also extends to scenarios with non-uniform file popularities and arbitrary mobility patterns.


2020 - Optimal Utility-Privacy Trade-Off with Total Variation Distance as a Privacy Measure [Articolo su rivista]
Rassouli, B.; Gunduz, D.
abstract

The total variation distance is proposed as a privacy measure in an information disclosure scenario when the goal is to reveal some information about available data in return of utility, while retaining the privacy of certain sensitive latent variables from the legitimate receiver. The total variation distance is introduced as a measure of privacy leakage by showing that: 1) it satisfies the post-processing and linkage inequalities, which makes it consistent with an intuitive notion of a privacy measure; 2) the optimal utility-privacy trade-off can be solved through a standard linear program when total variation distance is employed as the privacy measure; and 3) it provides a bound on the privacy leakage measured by mutual information, maximal leakage, or the improvement in an inference attack with a bounded cost function.


2020 - Privacy-Aware Time-Series Data Sharing with Deep Reinforcement Learning [Articolo su rivista]
Erdemir, E.; Dragotti, P. L.; Gunduz, D.
abstract

Internet of things (IoT) devices are becoming increasingly popular thanks to many new services and applications they offer. However, in addition to their many benefits, they raise privacy concerns since they share fine-grained time-series user data with untrusted third parties. In this work, we study the privacy-utility trade-off (PUT) in time-series data sharing. Existing approaches to PUT mainly focus on a single data point; however, temporal correlations in time-series data introduce new challenges. Methods that preserve the privacy for the current time may leak significant amount of information at the trace level as the adversary can exploit temporal correlations in a trace. We consider sharing the distorted version of a user's true data sequence with an untrusted third party. We measure the privacy leakage by the mutual information between the user's true data sequence and shared version. We consider both the instantaneous and average distortion between the two sequences, under a given distortion measure, as the utility loss metric. To tackle the history-dependent mutual information minimization, we reformulate the problem as a Markov decision process (MDP), and solve it using asynchronous actor-critic deep reinforcement learning (RL). We evaluate the performance of the proposed solution in location trace privacy on both synthetic and GeoLife GPS trajectory datasets. For the latter, we show the validity of our solution by testing the privacy of the released location trajectory against an adversary network.


2020 - Privacy-aware distributed hypothesis testing [Articolo su rivista]
Sreekumar, S.; Cohen, A.; Gunduz, D.
abstract

A distributed binary hypothesis testing (HT) problem involving two parties, a remote observer and a detector, is studied. The remote observer has access to a discrete memoryless source, and communicates its observations to the detector via a rate-limited noiseless channel. The detector observes another discrete memoryless source, and performs a binary hypothesis test on the joint distribution of its own observations with those of the observer. While the goal of the observer is to maximize the type II error exponent of the test for a given type I error probability constraint, it also wants to keep a private part of its observations as oblivious to the detector as possible. Considering both equivocation and average distortion under a causal disclosure assumption as possible measures of privacy, the trade-off between the communication rate from the observer to the detector, the type II error exponent, and privacy is studied. For the general HT problem, we establish single-letter inner bounds on both the rate-error exponent-equivocation and rate-error exponent-distortion trade-offs. Subsequently, single-letter characterizations for both trade-offs are obtained (i) for testing against conditional independence of the observer's observations from those of the detector, given some additional side information at the detector; and (ii) when the communication rate constraint over the channel is zero. Finally, we show by providing a counter-example where the strong converse which holds for distributed HT without a privacy constraint does not hold when a privacy constraint is imposed. This implies that in general, the rate-error exponent-equivocation and rate-error exponent-distortion trade-offs are not independent of the type I error probability constraint.


2020 - Semantic-Effectiveness Filtering and Control for Post-5G Wireless Connectivity [Articolo su rivista]
Popovski, P.; Simeone, O.; Boccardi, F.; Gunduz, D.; Sahin, O.
abstract

The traditional role of a communication engineer is to address the technical problem of transporting bits reliably over a noisy channel. With the emergence of 5G, and the availability of a variety of competing and coexisting wireless systems, wireless connectivity is becoming a commodity. This article argues that communication engineers in the post-5G era should extend the scope of their activity in terms of design objectives and constraints beyond connectivity to encompass the semantics of the transferred bits within the given applications and use cases. To provide a platform for semantic-aware connectivity solutions, this paper introduces the concept of a semantic-effectiveness (SE) plane as a core part of future communication architectures. The SE plane augments the protocol stack by providing standardized interfaces that enable information filtering and direct control of functionalities at all layers of the protocol stack. The advantages of the SE plane are described in the perspective of recent developments in 5G, and illustrated through a number of example applications. The introduction of a SE plane may help replacing the current “next-G paradigm” in wireless evolution with a framework based on continuous improvements and extensions of the systems and standards.


2020 - Straggler-aware distributed learning: Communication-computation latency trade-off [Articolo su rivista]
Ozfatura, E.; Ulukus, S.; Gunduz, D.
abstract

When gradient descent (GD) is scaled to many parallel workers for large-scale machine learning applications, its per-iteration computation time is limited by straggling workers. Straggling workers can be tolerated by assigning redundant computations and/or coding across data and computations, but in most existing schemes, each non-straggling worker transmits one message per iteration to the parameter server (PS) after completing all its computations. Imposing such a limitation results in two drawbacks: over-computation due to inaccurate prediction of the straggling behavior, and under-utilization due to discarding partial computations carried out by stragglers. To overcome these drawbacks, we consider multi-message communication (MMC) by allowing multiple computations to be conveyed from each worker per iteration, and propose novel straggler avoidance techniques for both coded computation and coded communication with MMC. We analyze how the proposed designs can be employed efficiently to seek a balance between the computation and communication latency. Furthermore, we identify the advantages and disadvantages of these designs in different settings through extensive simulations, both model-based and real implementation on Amazon EC2 servers, and demonstrate that proposed schemes with MMC can help improve upon existing straggler avoidance schemes.


2020 - Strong Converse for Testing Against Independence over a Noisy channel [Relazione in Atti di Convegno]
Sreekumar, S.; Gunduz, D.
abstract

A distributed binary hypothesis testing (HT) problem over a noisy (discrete and memoryless) channel studied previously by the authors is investigated from the perspective of the strong converse property. It was shown by Ahlswede and Csiszar that a strong converse holds in the above setting when the channel is rate-limited and noiseless. Motivated by this observation, we show that the strong converse continues to hold in the noisy channel setting for a special case of HT known as testing against independence (TAI), under the assumption that the channel transition matrix has non-zero elements. The proof utilizes the blowing up lemma and the recent change of measure technique of Tyagi and Watanabe as the key tools.


2020 - The Best Defense Is a Good Offense: Adversarial Attacks to Avoid Modulation Detection [Articolo su rivista]
Hameed, M. Z.; Gyorgy, A.; Gunduz, D.
abstract

We consider a communication scenario, in which an intruder tries to determine the modulation scheme of the intercepted signal. Our aim is to minimize the accuracy of the intruder, while guaranteeing that the intended receiver can still recover the underlying message with the highest reliability. This is achieved by perturbing channel input symbols at the encoder, similarly to adversarial attacks against classifiers in machine learning. In image classification, the perturbation is limited to be imperceptible to a human observer, while in our case the perturbation is constrained so that the message can still be reliably decoded by the legitimate receiver, which is oblivious to the perturbation. Simulation results demonstrate the viability of our approach to make wireless communication secure against state-of-the-art intruders (using deep learning or decision trees) with minimal sacrifice in the communication performance. On the other hand, we also demonstrate that using diverse training data and curriculum learning can significantly boost the accuracy of the intruder.


2019 - A Low-Complexity Cache-Aided Multi-Antenna Content Delivery Scheme [Relazione in Atti di Convegno]
Zhao, J.; Mohammadi Amiri, M.; Gunduz, D.
abstract

We study downlink beamforming in a single-cell network with a multi-antenna base station (BS) serving cache-enabled users. For a given common rate of the files in the system, we first formulate the minimum transmit power with beamforming at the BS as a non-convex optimization problem. This corresponds to a multiple multicast problem, to which a stationary solution can be efficiently obtained through successive convex approximation (SCA). It is observed that the complexity of the problem grows exponentially with the number of subfiles delivered to each user in each time slot, which itself grows exponentially with the number of users in the system. Therefore, we introduce a low-complexity alternative through time-sharing that limits the number of subfiles that can be received by a user in each time slot. It is shown through numerical simulations that, the reduced-complexity beamforming scheme has minimal performance gap compared to transmitting all the subfiles jointly, and outperforms the state-of-the-art low-complexity scheme at all SNR and rate values with sufficient spatial degrees of freedom, and in the high SNR/high rate regime when the number of spatial degrees of freedom is limited.


2019 - Audience-Retention-Rate-Aware Caching and Coded Video Delivery with Asynchronous Demands [Articolo su rivista]
Yang, Q.; Mohammadi Amiri, M.; Gunduz, D.
abstract

Most of the current literature on coded caching focus on a static scenario in which a fixed number of users synchronously place their requests from a content library, and the performance is measured in terms of the latency in satisfying all of these requests. In practice, however, users start watching an online video content asynchronously over time, and often abort watching a video before it is completed. The latter behavior is captured by the notion of audience retention rate, which measures the portion of a video content watched on average. In order to bring coded caching one step closer to practice, asynchronous user demands are considered in this paper by allowing user demands to arrive randomly over time, and both the popularity of video files, and the audience retention rates are taken into account. A decentralized partial coded delivery (PCD) scheme is proposed, and two cache allocation schemes are employed; namely homogeneous cache allocation (HoCA) and heterogeneous cache allocation (HeCA), which allocate users' caches among different chunks of the video files in the library. Numerical results validate that the proposed PCD scheme, either with HoCA or HeCA, outperforms conventional uncoded caching as well as the state-of-the-art decentralized caching schemes, which consider only the file popularities, and are designed for synchronous demand arrivals. An information-theoretical lower bound on the average delivery rate is also presented.


2019 - Automatic Modulation Classification in the Presence of Interference [Relazione in Atti di Convegno]
Triantaris, P.; Tsimbalo, E.; Chin, W. H.; Gunduz, D.
abstract

A modulation recognition method based on a con-volutional neural network (CNN) architecture is assessed through classification of synthetic baseband signals in the presence of a second interfering signal source. The complexity and adaptability of CNNs is leveraged so as to forgo statistical feature extraction procedures and efficiently classify based on raw signals or their modified forms. Both scenarios with the interfering signal's modulation scheme known and unknown, are considered. Simulation results show that the CNN architecture achieves considerable accuracy despite the presence of interference, and the knowledge of the modulation scheme of the interfering signal significantly improves the accuracy.


2019 - Average Age-of-Information with a Backup Information Source [Relazione in Atti di Convegno]
Gindullina, E.; Badia, L.; Gunduz, D.
abstract

Data collected and transmitted by Internet of things (IoT) devices are typically used for control and monitoring purposes; and hence, their timely delivery is of utmost importance for the underlying applications. However, IoT devices operate with very limited energy sources, severely reducing their ability for timely collection and processing of status updates. IoT systems make up for these limitations by employing multiple low-power low-complexity devices that can monitor the same signal, possibly with different quality observations and different energy costs, to create diversity against the limitations of individual nodes. We investigate policies to minimize the average age of information (AoI) in a monitoring system that collects data from two sources of information denoted as primary and backup sources, respectively. We assume that each source offers a different trade-off between the AoI and the energy cost. The monitoring node is equipped with a finite size battery and harvests ambient energy. For this setup, we formulate the scheduling of status updates from the two sources as a Markov decision process (MDP), and obtain a policy that decides on the optimal action to take (i.e., which source to query or remain idle) depending on the current energy level and AoI. The performance of the obtained policy is compared with an aggressive policy for different system parameters. We identify few types of optimal solution structures and discuss the benefits of having a backup source of information in the system.


2019 - Average age of information with hybrid ARQ under a resource constraint [Articolo su rivista]
Ceran, E. T.; Gunduz, D.; Gyorgy, A.
abstract

Scheduling the transmission of status updates over an error-prone communication channel is studied in order to minimize the long-term average age of information at the destination under a constraint on the average number of transmissions at the source node. After each transmission, the source receives an instantaneous ACK/NACK feedback, and decides on the next update without prior knowledge on the success of future transmissions. The optimal scheduling policy is first studied under different feedback mechanisms when the channel statistics are known; in particular, the standard automatic repeat request (ARQ) and hybrid ARQ (HARQ) protocols are considered. The structural results are derived for the optimal policy under HARQ, while the optimal policy is determined analytically for ARQ. For the case of unknown environments, an average-cost reinforcement learning algorithm is proposed that learns the system parameters and the transmission policy in real time. The effectiveness of the proposed methods is verified through the numerical results.


2019 - Coded Caching with Asymmetric Cache Sizes and Link Qualities: The Two-User Case [Articolo su rivista]
Cao, D.; Zhang, D.; Chen, P.; Liu, N.; Kang, W.; Gunduz, D.
abstract

The centralized coded caching problem is studied for the two-user scenario, considering heterogeneous cache capacities at the users and private channels from the server to the users, in addition to a shared channel. Optimal caching and delivery strategies that minimize the worst-case delivery latency are presented for an arbitrary number of files. The converse proof follows from the sufficiency of file-index-symmetric caching and delivery codes, while the achievability is obtained through memory-sharing among a number of special memory-capacity pairs. The optimal scheme is shown to exploit the private link capacities by transmitting part of the corresponding user's request in an uncoded fashion. When there are no private links, the results presented here improve upon the two known results in the literature, namely: 1) equal cache capacities and arbitrary number of files and 2) unequal cache capacities and two files. The results are then extended to the caching problem with heterogeneous distortion requirements.


2019 - Collaborative machine learning at the wireless edge with blind transmitters [Relazione in Atti di Convegno]
Mohammadi Amiri, M.; Duman, T. M.; Gunduz, D.
abstract

We study wireless collaborative machine learning (ML), where mobile edge devices, each with its own dataset, carry out distributed stochastic gradient descent (DSGD) over-the-air with the help of a wireless access point acting as the parameter server (PS). At each iteration of the DSGD algorithm wireless devices compute gradient estimates with their local datasets, and send them to the PS over a wireless fading multiple access channel (MAC). Motivated by the additive nature of the wireless MAC, we propose an analog DSGD scheme, in which the devices transmit scaled versions of their gradient estimates in an uncoded fashion. We assume that the channel state information (CSI) is available only at the PS. We instead allow the PS to employ multiple antennas to alleviate the destructive fading effect, which cannot be cancelled by the transmitters due to the lack of CSI. Theoretical analysis indicates that, with the proposed DSGD scheme, increasing the number of PS antennas mitigates the fading effect, and, in the limit, the effects of fading and noise disappear, and the PS receives aligned signals used to update the model parameter. The theoretical results are then corroborated with the experimental ones.


2019 - Communication without interception: Defense against modulation detection [Relazione in Atti di Convegno]
Hameed, M. Z.; Gyorgy, A.; Gunduz, D.
abstract

We consider a communication scenario, in which an intruder tries to determine the modulation scheme of the intercepted signal. Our aim is to minimize the accuracy of the intruder, while guaranteeing that the intended receiver can still recover the underlying message with the highest reliability. This is achieved by constellation perturbation at the encoder, similarly to adversarial attacks against classifiers in machine learning. In image classification, the perturbation is limited to be imperceptible to a human observer, while in our case the perturbation is constrained so that the message can still be reliably decoded by a legitimate receiver that is oblivious to the perturbation. Simulation results demonstrate the viability of our approach to make wireless communication secure against both state-of-the-art deep-learning- and decision-tree-based intruders with minimal sacrifice in the communication performance.


2019 - Computation Scheduling for Distributed Machine Learning with Straggling Workers [Relazione in Atti di Convegno]
Mohammadi Amiri, M.; Gunduz, D.
abstract

We study scheduling of computation tasks across n workers in a large scale distributed learning problem. Computation speeds of the workers are assumed to be heterogeneous and unknown to the master, and redundant computations are assigned to the workers in order to tolerate straggling workers. We consider sequential computation and instantaneous communication from each worker to the master, and each computation round, which can model a single iteration of the stochastic gradient descent (SGD) algorithm, is completed once the master receives k ≤ n distinct computations, referred to as the computation target. Our goal is to characterize the average completion time as a function of the computation load, which denotes the portion of the dataset available at each worker, and the computation target. We propose two computation scheduling schemes that specify the computation tasks assigned to each worker, as well as their order of execution. We also establish a lower bound on the minimum average completion time. Numerical results show a significant reduction in the average computation time over the existing coded and uncoded computing schemes.


2019 - Computation scheduling for distributed machine learning with straggling workers [Articolo su rivista]
Mohammadi Amiri, M.; Gunduz, D.
abstract

We study scheduling of computation tasks across n workers in a large scale distributed learning problem with the help of a master. Computation and communication delays are assumed to be random, and redundant computations are assigned to workers in order to tolerate stragglers. We consider sequential computation of tasks assigned to a worker, while the result of each computation is sent to the master right after its completion. Each computation round, which can model an iteration of the stochastic gradient descent (SGD) algorithm, is completed once the master receives k distinct computations, referred to as the computation target. Our goal is to characterize the average completion time as a function of the computation load, which denotes the portion of the dataset available at each worker, and the computation target. We propose two computation scheduling schemes that specify the tasks assigned to each worker, as well as their computation schedule, i.e., the order of execution. Assuming a general statistical model for computation and communication delays, we derive the average completion time of the proposed schemes. We also establish a lower bound on the minimum average completion time by assuming prior knowledge of the random delays. Experimental results carried out on Amazon EC2 cluster show a significant reduction in the average completion time over existing coded and uncoded computing schemes. It is also shown numerically that the gap between the proposed scheme and the lower bound is relatively small, confirming the efficiency of the proposed scheduling design.


2019 - Content caching and delivery in wireless radio access networks [Articolo su rivista]
Tao, M.; Gunduz, D.; Fan, X.; Pujol Roig, J. S.
abstract

Today's mobile data traffic is dominated by content-oriented traffic. Caching popular contents at the network edge can alleviate network congestion and reduce content delivery latency. This paper provides a comprehensive and unified study of caching and delivery techniques in wireless radio access networks (RANs) with caches at all edge nodes (ENs) and user equipments (UEs). Three cache-aided RAN architectures are considered: RANs without fronthaul, with dedicated fronthaul, and with wireless fronthaul. It first reviews in a tutorial nature how caching facilitates interference management in these networks by enabling interference cancelation (IC), zero-forcing (ZF), and interference alignment (IA). Then, two new delivery schemes are presented. One is for RANs with dedicated fronthaul, which considers centralized cache placement at the ENs but both centralized and decentralized placement at the UEs. This scheme combines IA, ZF, and IC together with soft-transfer fronthauling. The other is for RANs with wireless fronthaul, which considers decentralized cache placement at all nodes. It leverages the broadcast nature of wireless fronthaul to fetch not only uncached but also cached contents to boost transmission cooperation among the ENs. The numerical results show that both schemes outperform existing results for a wide range of system parameters, thanks to the various caching gains obtained opportunistically.


2019 - Deep Convolutional Compression for Massive MIMO CSI Feedback [Relazione in Atti di Convegno]
Yang, Q.; Boloursaz Mashhadi, M.; Gunduz, D.
abstract

Massive multiple-input multiple-output (MIMO) systems require downlink channel state information (CSI) at the base station (BS) to better utilize the available spatial diversity and multiplexing gains. However, in a frequency division duplex (FDD) massive MIMO system, the huge CSI feedback overhead becomes restrictive and degrades the overall spectral efficiency. In this paper, we propose a deep learning based channel state matrix compression scheme, called DeepCMC, composed of convolutional layers followed by quantization and entropy coding blocks. Simulation results demonstrate that DeepCMC significantly outperforms the state of the art compression schemes in terms of the reconstruction quality of the channel state matrix for the same compression rate, measured in bits per channel dimension.


2019 - Deep Joint Source-Channel Coding for Wireless Image Transmission [Articolo su rivista]
Bourtsoulatze, E; Kurka, Db; Gunduz, D
abstract

We propose a joint source and channel coding (JSCC) technique for wireless image transmission that does not rely on explicit codes for either compression or error correction; instead, it directly maps the image pixel values to the complex-valued channel input symbols. We parameterize the encoder and decoder functions by two convolutional neural networks (CNNs), which are trained jointly, and can be considered as an autoencoder with a non-trainable layer in the middle that represents the noisy communication channel. Our results show that the proposed deep JSCC scheme outperforms digital transmission concatenating JPEG or JPEG2000 compression with a capacity achieving channel code at low signal-to-noise ratio (SNR) and channel bandwidth values in the presence of additive white Gaussian noise (AWGN). More strikingly, deep JSCC does not suffer from the "cliff effect," and it provides a graceful performance degradation as the channel SNR varies with respect to the SNR value assumed during training. In the case of a slow Rayleigh fading channel, deep JSCC learns noise resilient coded representations and significantly outperforms separation-based digital communication at all SNR and channel bandwidth values.


2019 - Deep Joint Source-channel Coding for Wireless Image Transmission [Relazione in Atti di Convegno]
Bourtsoulatze, Eirina; Burth Kurka, David; Gunduz, Deniz
abstract

We propose a novel joint source and channel coding (JSCC) scheme for wireless image transmission that departs from the conventional use of explicit source and channel codes for compression and error correction, and directly maps the image pixel values to the complex-valued channel input signal. Our encoder-decoder pair form an autoencoder with a non-trainable layer in the middle, which represents the noisy communication channel. Our results show that the proposed deep JSCC scheme outperforms separation-based digital transmission at low signal-to-noise ratio (SNR) and low channel bandwidth regimes in the presence of additive white Gaussian noise (AWGN). More strikingly, deep JSCC does not suffer from the cliff effect as the channel SNR varies with respect to the SNR value assumed during training. In the case of a slow Rayleigh fading channel, deep JSCC can learn to communicate without explicit pilot signals or channel estimation, and significantly outperforms separation-based digital communication at all SNR and channel bandwidth values.


2019 - Distributed Gradient Descent with Coded Partial Gradient Computations [Relazione in Atti di Convegno]
Ozfatura, E.; Ulukus, S.; Gunduz, D.
abstract

Coded computation techniques provide robustness against straggling servers in distributed computing, with the following limitations: First, they increase decoding complexity. Second, they ignore computations carried out by straggling servers; and they are typically designed to recover the full gradient, and thus, cannot provide a balance between the accuracy of the gradient and per-iteration completion time. Here we introduce a hybrid approach, called coded partial gradient computation (CPGC), that benefits from the advantages of both coded and uncoded computation schemes, and reduces both the computation time and decoding complexity.


2019 - Distributed hypothesis testing under privacy constraints [Relazione in Atti di Convegno]
Sreekumar, S.; Gunduz, D.; Cohen, A.
abstract

A distributed binary hypothesis testing problem involving two parties, a remote observer and a detector, is studied. The remote observer has access to a discrete memoryless source, and communicates its observations to the detector via a rate-limited noiseless channel. The detector tests for the independence of its own observations with that of the observer, conditioned on some additional side information. While the goal is to maximize the type 2 error exponent of the test for a given type 1 error probability constraint, it is also desired to keep a private part, which is correlated with the observer's observations, as oblivious to the detector as possible. Considering equivocation and average distortion as the metrics of privacy at the detector, a tight single-letter characterization of the rate-error exponent-equivocation and rate-error exponent-distortion tradeoff is obtained.


2019 - Dynamic Content Updates in Heterogeneous Wireless Networks [Relazione in Atti di Convegno]
Abad, M. S. H.; Ozfatura, E.; Ercetin, O.; Gunduz, D.
abstract

Content storage at the network edge is a promising solution to mitigate excessive content traffic. To this end, cache-enabled cellular architectures can be utilized to reduce the network cost. However, content storage strategies should be able to take into account user satisfaction, which depends on the age of a dynamic content. The ratio of satisfied users can be increased with more frequent cache refreshment, albeit at an increased network cost. In this paper, we introduce a cache refreshment strategy that strikes a balance between user satisfaction and the infrastructure cost.


2019 - Gradient Coding with Clustering and Multi-Message Communication [Relazione in Atti di Convegno]
Ozfatura, E.; Gunduz, D.; Ulukus, S.
abstract

Gradient descent (GD) methods are commonly employed in machine learning problems to optimize the parameters of the model in an iterative fashion. For problems with massive datasets, computations are distributed to many parallel computing servers (i.e., workers) to speed up GD iterations. While distributed computing can increase the computation speed significantly, the per-iteration completion time is limited by the slowest straggling workers. Coded distributed computing can mitigate straggling workers by introducing redundant computations; however, existing coded computing schemes are mainly designed against persistent stragglers, and partial computations at straggling workers are discarded, leading to wasted computational capacity. In this paper, we propose a novel gradient coding (GC) scheme which allows multiple coded computations to be conveyed from each worker to the master per iteration. We numerically show that the proposed GC with multi-message communication (MMC) together with clustering provides significant improvements in the average completion time (of each iteration), with minimal or no increase in the communication load.


2019 - Guest Editorial Special Issue on Machine Learning in Wireless Communication - Part i [Articolo su rivista]
Gesbert, D.; Gunduz, D.; de Kerret, P.; Murthy, C.; van der Schaar, M.; Sidiroupoulos, N.
abstract

Machine learning and data driven approaches have recently received much attention as a key enabler for future 5G and beyond wireless networks. Yet, the evolution towards learning-based data driven networks is still in its infancy, and much of the realization of the promised benefits requires thorough research and development. Fundamental questions remain as to where and how ML can really complement the well-established, well-tested communication systems designed over the last four decades. Moreover, adaptation of machine learning methods is likely needed to realize their full potential in the wireless context. This is particularly challenging for the lower layers of the protocol stack, where the constraints, problem formulation, and even the objectives may fundamentally differ from the typical scenarios to which machine learning has been successfully applied in recent years. In addition, a thorough understanding of the fundamental performance limits is also essential in order to establish quality-of-service guarantees that are common in communication system design. Such challenges, which lie at the core of the special issue, can be categorized into a number of research topics ranging from the optization of neural networks architectures that are suited to wireless communication links (inclusing autoencoders, generative adversarial networks, reinforcement based networks etc) to performance analysis, to the acceleration of data-driven training, and possibly in distributed settings. The application domains within the wireless realm are also quite diverse in nature with promising preliminary results in the area of physical layer design and resource allocation as well as for network service orchestrations. Testbeds and experimental evaluations are also begining to be reported.


2019 - Guest Editorial Special Issue on Machine Learning in Wireless Communication-Part 2 [Articolo su rivista]
Gesbert, D.; Gunduz, D.; de Kerret, P.; Murthy, C.; van der Schaar, M.; Sidiroupoulos, N.
abstract


2019 - Heterogeneous coded computation across heterogeneous workers [Relazione in Atti di Convegno]
Sun, Y.; Zhao, J.; Zhou, S.; Gunduz, D.
abstract

Coded distributed computing framework enables large-scale machine learning (ML) models to be trained efficiently in a distributed manner, while mitigating the straggler effect. In this work, we consider a multi-task assignment problem in a coded distributed computing system, where multiple masters, each with a different matrix multiplication task, assign computation tasks to workers with heterogeneous computing capabilities. Both dedicated and probabilistic worker assignment models are considered, with the objective of minimizing the average completion time of all tasks. For dedicated worker assignment, greedy algorithms are proposed and the corresponding optimal load allocation is derived based on the Lagrange multiplier method. For probabilistic assignment, successive convex approximation method is used to solve the non-convex optimization problem. Simulation results show that the proposed algorithms reduce the completion time by 80% over uncoded scheme, and 49% over an unbalanced coded scheme.


2019 - Hypothesis Testing over a Noisy Channel [Relazione in Atti di Convegno]
Sreekumar, S.; Gunduz, D.
abstract

A point to point hypothesis testing problem involving two parties, one referred to as the observer and the other as the detector, is studied. The observer observes a discrete memoryless source and communicates its observations to the detector over a discrete memoryless channel. The detector performs a binary hypothesis test on the probability distribution of the observer's observation. The trade-off between the type 1 error probability and the type 2 error exponent is explored. We obtain a single-letter characterization of the optimal type 2 error exponent for a given constraint on the type 1 error probability. We also show that a strong converse holds, in the sense that, the optimal type 2 error exponent is independent of the constraint on the type 1 error probability.


2019 - Latent feature disclosure under perfect sample privacy [Relazione in Atti di Convegno]
Rassouli, B.; Rosas, F.; Gunduz, D.
abstract

Guaranteeing perfect data privacy seems to be incompatible with the economical and scientific opportunities provided by extensive data collection and processing. This paper tackles this challenge by studying how to disclose latent features of data sets without compromising the privacy of individual data samples. We leverage counter-intuitive properties of the multivariate statistics of data samples, and propose a technique to disclose collective properties of data sets while keeping each data sample confidential. For a given statistical description of the data set, we show how to build an optimal disclosure strategy/mapping using linear programming techniques. We provide necessary and sufficient conditions that determine when our approach is feasible, and illustrate the optimal solution in some simple scenarios. We observe that the disclosure strategy may be independent of the latent feature in some scenarios, for which explicit expressions for the performance are provided.


2019 - Machine Learning at the Wireless Edge: Distributed Stochastic Gradient Descent Over-the-Air [Relazione in Atti di Convegno]
Mohammadi Amiri, M.; Gunduz, D.
abstract

We study collaborative machine learning at the wireless edge, where power and bandwidth-limited devices (workers), with limited local datasets, implement distributed stochastic gradient descent (DSGD) over-the-air with the help of a remote parameter server (PS). We consider a wireless multiple access channel (MAC) from the workers to the PS for communicating the local gradient estimates. We first introduce a digital DSGD (D-DSGD) scheme, assuming that the workers operate on the boundary of the MAC capacity region at each iteration of the DSGD algorithm, and digitize their estimates within the bit budget allowed by the employed power allocation. We then introduce an analog scheme, called A-DSGD, motivated by the additive nature of the wireless MAC, where the workers send their gradient estimates over the MAC through the available channel bandwidth without employing any digital code. Numerical results show that A-DSGD converges much faster than D-DSGD. The improvement is particularly compelling at low power and low bandwidth regimes. We also observe that the performance of A-DSGD improves with the number of workers, while D-DSGD deteriorates, limiting the ability of the latter in harnessing the computation power of many edge devices.


2019 - Machine Learning in the Air [Articolo su rivista]
Gunduz, D.; de Kerret, P.; Sidiroupoulos, N.; Gesbert, D.; Murthy, C.; van der Schaar, M.
abstract

Thanks to the recent advances in processing speed, data acquisition and storage, machine learning (ML) is penetrating every facet of our lives, and transforming research in many areas in a fundamental manner. Wireless communications is another success story - ubiquitous in our lives, from handheld devices to wearables, smart homes, and automobiles. While recent years have seen a flurry of research activity in exploiting ML tools for various wireless communication problems, the impact of these techniques in practical communication systems and standards is yet to be seen. In this paper, we review some of the major promises and challenges of ML in wireless communication systems, focusing mainly on the physical layer. We present some of the most striking recent accomplishments that ML techniques have achieved with respect to classical approaches, and point to promising research directions where ML is likely to make the biggest impact in the near future. We also highlight the complementary problem of designing physical layer techniques to enable distributed ML at the wireless network edge, which further emphasizes the need to understand and connect ML with fundamental concepts in wireless communications.


2019 - Multicast-Aware Proactive Caching in Wireless Networks with Deep Reinforcement Learning [Relazione in Atti di Convegno]
Somuyiwa, S. O.; Gyorgy, A.; Gunduz, D.
abstract

We consider mobile users randomly requesting contents from a single dynamic content library. A random number of contents are added to the library at every time instant and each content has a lifetime, after which it becomes irrelevant to the users, and a class-specific request probability with which a user may request it. Multiple requests for a single content are served through a common multicast transmission. Contents can also be proactively stored, before they are requested, in finite capacity cache memories at the user equipment. Any time a content is transmitted to some users, a cost, which depends on the number of bits transmitted and the channel states of the receiving users at that time instant, is incurred by the system. The goal is to minimize the long term expected average cost. We model the problem as a Markov decision process and propose a deep reinforcement learning (DRL)-based policy to solve it. The DRL-based policy employs the deep deterministic policy gradient method for training to minimize the long term average cost. We evaluate the performance of the proposed scheme in comparison to traditional reactive multicast transmission and other multicast-aware caching schemes, and show that the proposed scheme provides significant performance gains.


2019 - Optimal Privacy-Utility Trade-off under a Rate Constraint [Relazione in Atti di Convegno]
Sreekumar, Sreejith; Gunduz, Deniz
abstract

We study the privacy-utility trade-off in data release under a rate constraint. An agent observes random variable X and reveals information U to the utility provider over a rate-constrained channel, such that I(X; U) ≤ R, in return for utility I(U; Y ), where Y denotes a latent random variable correlated with X. While the objective is to maximize the utility, the agent also wants to protect a private information S, also correlated with X and Y from the utility provider. The trade-off between rate, utility and private information leakage is studied. This problem can be thought of as a generalization of both the information bottleneck and privacy funnel problems, reducing to either of the two problems in special cases. A necessary and sufficient condition for the existence of positive utility under zero private information leakage (or perfect privacy) is established. Subsequently, the problem of maximizing the utility subject to perfect privacy constraint is shown to be a linear program when the rate constraint is inactive. Also, the maximum value of the ratio of utility to infinitesimal private information leakage for an arbitrary rate constraint is obtained.


2019 - Optimal utility-privacy trade-off with total variation distance as a privacy measure [Relazione in Atti di Convegno]
Rassouli, B.; Gunduz, D.
abstract

The total variation distance is proposed as a privacy measure in an information disclosure scenario when the goal is to reveal some information about available data in order to receive utility, while preserving the privacy of sensitive data from the legitimate receiver. The total variation distance is motivated as a measure of privacy-leakage by showing that: i) it satisfies the post-processing and linkage inequalities, which makes it consistent with an intuitive notion of a privacy measure; ii) the optimal utility-privacy trade-off can be solved through a standard linear program when total variation distance is employed as the privacy measure; iii) it provides a bound on the privacy-leakage measured by mutual information, maximal leakage, or the improvement in an inference attack with an arbitrary bounded cost function.


2019 - Over-the-Air Machine Learning at the Wireless Edge [Relazione in Atti di Convegno]
Mohammadi Amiri, M.; Gunduz, D.
abstract

We study distributed machine learning at the wireless edge, where limited power devices (workers) with local datasets implement distributed stochastic gradient descent (DSGD) over-the-air with the help of a remote parameter server (PS). We consider a bandwidth-limited fading multiple access channel (MAC) from the workers to the PS for communicating the local gradient estimates. Motivated by the additive nature of the wireless MAC, we study analog transmission of low-dimensional gradient estimates while accumulating error from previous iterations. We also design an opportunistic worker scheduling scheme to align the received gradient vectors at the PS in an efficient manner. Numerical results show that the proposed DSGD algorithm converges much faster than the state-of-the-art, while also providing a significantly higher accuracy.


2019 - Privacy Against Brute-Force Inference Attacks [Relazione in Atti di Convegno]
Seyed Ali Osia, ; Borzoo, Rassouli; Hamed, Haddadi; Rabiee, Hamid R.; Gunduz, Deniz
abstract

Privacy-preserving data release is about disclosing information about useful data while retaining the privacy of sensitive data. Assuming that the sensitive data is threatened by a brute-force adversary, we define Guessing Leakage as a measure of privacy, based on the concept of guessing. After investigating the properties of this measure, we derive the optimal utility-privacy trade-off via a linear program with any f-information adopted as the utility measure, and show that the optimal utility is a concave and piece-wise linear function of the privacy-leakage budget.


2019 - Privacy against a hypothesis testing adversary [Articolo su rivista]
Li, Z.; Oechtering, T.; Gunduz, D.
abstract

Privacy against an adversary (AD) that tries to detect the underlying privacy-sensitive data distribution is studied. The original data sequence is assumed to come from one of the two known distributions, and the privacy leakage is measured by the probability of error of the binary hypothesis test carried out by the AD. A management unit (MU) is allowed to manipulate the original data sequence in an online fashion while satisfying an average distortion constraint. The goal of the MU is to maximize the minimal type II probability of error subject to a constraint on the type I probability of error assuming an adversarial Neyman-Pearson test, or to maximize the minimal error probability assuming an adversarial Bayesian test. The asymptotic exponents of the maximum minimal type II probability of error and the maximum minimal error probability are shown to be characterized by a Kullback-Leibler divergence rate and a Chernoff information rate, respectively. Privacy performances of particular management policies, the memoryless hypothesis-aware policy and the hypothesis-unaware policy with memory, are compared. The proposed formulation can also model adversarial example generation with minimal data manipulation to fool classifiers. At last, the results are applied to a smart meter privacy problem, where the user's energy consumption is manipulated by adaptively using a renewable energy source in order to hide user's activity from the energy provider.


2019 - Privacy-Aware Location Sharing with Deep Reinforcement Learning [Relazione in Atti di Convegno]
Erdemir, E.; Dragotti, P. L.; Gunduz, D.
abstract

Location-based services (LBSs) have become widely popular. Despite their utility, these services raise concerns for privacy since they require sharing location information with untrusted third parties. In this work, we study privacy-utility trade-off in location sharing mechanisms. Existing approaches are mainly focused on privacy of sharing a single location or myopic location trace privacy; neither of them taking into account the temporal correlations between the past and current locations. Although these methods preserve the privacy for the current time, they may leak significant amount of information at the trace level as the adversary can exploit temporal correlations in a trace. We propose an information theoretically optimal privacy preserving location release mechanism that takes temporal correlations into account. We measure the privacy leakage by the mutual information between the user's true and released location traces. To tackle the history-dependent mutual information minimization, we reformulate the problem as a Markov decision process (MDP), and solve it using asynchronous actor-critic deep reinforcement learning (RL).


2019 - Privacy-cost Trade-off in a Smart Meter System with a Renewable Energy Source and a Rechargeable Battery [Relazione in Atti di Convegno]
Erdemir, E.; Dragotti, P. L.; Gunduz, D.
abstract

We study the privacy-cost trade-off in a smart meter (SM) system with a renewable energy source (RES) and a finite-capacity rechargeable battery (RB). Privacy is measured by the mutual information rate between the energy demand and the energy received from the grid, where the latter also determines the cost, and hence, reported by the SM to the utility provider (UP). We consider a renewable energy generation process that fully charges the RB at random time instants, and its realization is assumed to be known also by the UP. We reformulate the problem as a Markov decision process (MDP), and solve it by dynamic programming (DP) to design battery charging and discharging policies that minimize a linear combination of the privacy leakage and energy cost. We also propose a lower bound and two alternative low-complexity energy management policies, one of which is shown numerically to perform close to the MDP solution.


2019 - Reinforcement Learning to Minimize Age of Information with an Energy Harvesting Sensor with HARQ and Sensing Cost [Relazione in Atti di Convegno]
Tugce Ceran, Elif; Gunduz, Deniz; Gyorgy, Andras
abstract

The time average expected age of information (AoI) is studied for status updates sent from an energy-harvesting transmitter with a finite-capacity battery. The optimal scheduling policy is first studied under different feedback mechanisms when the channel and energy harvesting statistics are known. For the case of unknown environments, an average-cost reinforcement learning algorithm is proposed that learns the system parameters and the status update policy in real time. The effectiveness of the proposed methods is verified through numerical results.


2019 - Smart meter privacy [Capitolo/Saggio]
Erdemir, E.; Gunduz, D.; Dragotti, P. L.
abstract

The newgeneration electricity supply network, called the smart grid (SG), provides consumers with an active management and control of the power. By utilizing digital communications and sensing technologies which make the grid smart, SGs yield more efficient electricity transmission, reduced peak demand, improved security and increased integration of renewable energy systems compared to the traditional grid. Smart meters (SMs) are one of the core enablers of SG systems; they measure and record the high resolution electricity consumption information of a household almost in a real time basis, and report it to the utility provider (UP) at regular time intervals. SM measurements can be used for time-of-use pricing, trading user-generated energy, and mitigating load variations. However, real-time SM readings can also reveal sensitive information about the consumer’s activities which the user may not want to share with the UP, resulting in serious privacy concerns. SM privacy enabling techniques proposed in the literature can be categorized as SM data manipulation and demand shaping. While the SMdata is modified before being reported to the UP in the former method, the latter requires direct manipulation of the real energy consumption by exploiting physical resources, such as a renewable energy source (RES) or a rechargeable battery (RB). In this chapter, a datamanipulation privacy-enabling technique and three different demand shaping privacy-enabling techniques are presented, considering SM with a RES and an RB, SM with only an RB andSMwith only a RES. Information theoretic measures are used to quantify SM privacy. Optimal energy management strategies and bounds which are obtained using control theory, specifically Markov decision processes (MDPs), and rate distortion theory are analyzed.


2019 - Speeding Up Distributed Gradient Descent by Utilizing Non-persistent Stragglers [Relazione in Atti di Convegno]
Ozfatura, E.; Gunduz, D.; Ulukus, S.
abstract

When gradient descent (GD) is scaled to many parallel computing servers (workers) for large scale machine learning problems, its per-iteration computation time is limited by the straggling workers. Coded distributed GD (DGD) can tolerate straggling workers by assigning redundant computations to the workers, but in most existing schemes, each non-straggling worker transmits one message per iteration to the parameter server (master) after completing all its computations. We allow multiple computations to be conveyed from each worker per iteration in order to exploit computations executed also by the straggling worker. We show that the average completion time per iteration can be reduced significantly at a reasonable increase in the communication load. We also propose a general coded DGD technique which can trade-off the average computation time with the communication load.


2019 - Storage-repair bandwidth trade-off for wireless caching with partial failure and broadcast repair [Relazione in Atti di Convegno]
Mital, N.; Kralevska, K.; Ling, C.; Gunduz, D.
abstract

Repair of multiple partially failed cache nodes is studied in a distributed wireless content caching system, where r out of a total of n cache nodes lose part of their cached data. Broadcast repair of failed cache contents at the network edge is studied; that is, the surviving cache nodes transmit broadcast messages to the failed ones, which are then used, together with the surviving data in their local cache memories, to recover the lost content. The trade-off between the storage capacity and the repair bandwidth is derived. It is shown that utilizing the broadcast nature of the wireless medium and the surviving cache contents at partially failed nodes significantly reduces the required repair bandwidth per node.


2019 - Successive Refinement of Images with Deep Joint Source-Channel Coding [Relazione in Atti di Convegno]
Burth Kurka, D.; Gunduz, D.
abstract

We introduce deep learning based communication methods for successive refinement of images over wireless channels. We present three different strategies for progressive image transmission with deep JSCC, with different complexity-performance tradeoffs, all based on convolutional autoencoders. Numerical results show that deep JSCC not only provides graceful degradation with channel signal-to-noise ratio (SNR) and improved performance in low SNR and low bandwidth regimes compared to state-of-the-art digital communication techniques, but can also successfully learn a layered representation, achieving performance close to a single-layer scheme. These results suggest that natural images encoded with deep JSCC over Gaussian channels are almost successively refinable.


2018 - A Reinforcement Learning Approach to Age of Information in Multi-User Networks [Relazione in Atti di Convegno]
Ceran, E. T.; Gunduz, D.; Gyorgy, A.
abstract

Scheduling the transmission of time-sensitive data to multiple users over error-prone communication channels is studied with the goal of minimizing the longterm average age of information (AoI) at the users under a constraint on the average number of transmissions. The source can transmit only to a single user at each time slot, and after each transmission, it receives an instantaneous ACK/NACK feedback from the intended receiver, and decides on when and to which user to transmit the next update. The optimal scheduling policy is first studied under different feedback mechanisms when the channel statistics are known; in particular, the standard automatic repeat request (ARQ) and hybrid ARQ (HARQ) protocols are considered. Then a reinforcement learning (RL) approach is introduced, which does not assume any a priori information on the random processes governing the channel states. Different RL methods are applied and compared through numerical simulations.


2018 - A Reinforcement-Learning Approach to Proactive Caching in Wireless Networks [Articolo su rivista]
Somuyiwa, S. O.; Gyorgy, A.; Gunduz, D.
abstract

We consider a mobile user accessing contents in a dynamic environment, where new contents are generated over time (by the user's contacts) and remain relevant to the user for random lifetimes. The user, equipped with a finite-capacity cache memory, randomly accesses the system and requests all the relevant contents at the time of access. The system incurs an energy cost associated with the number of contents downloaded and the channel quality at that time. Assuming causal knowledge of the channel quality, the content profile, and the user-access behavior, we model the proactive caching problem as a Markov decision process with the goal of minimizing the long-term average energy cost. We first prove the optimality of a threshold-based proactive caching scheme, which dynamically caches or removes appropriate contents from the memory, prior to being requested by the user, depending on the channel state. The optimal threshold values depend on the system state and hence are computationally intractable. Therefore, we propose parametric representations for the threshold values and use reinforcement-learning algorithms to find near-optimal parameterizations. We demonstrate through simulations that the proposed schemes significantly outperform classical reactive downloading and perform very close to a genie-aided lower bound.


2018 - Average age of information with hybrid ARQ under a resource constraint [Relazione in Atti di Convegno]
Ceran, E. T.; Gunduz, D.; Gyorgy, A.
abstract

Scheduling the transmission of status updates over an error-prone communication channel is studied in order to minimize the long-term average age of information (AoI) at the destination under a constraint on the average number of transmissions at the source node. After each transmission, the source receives an instantaneous ACK/NACK feedback, and decides on the next update without prior knowledge on the success of future transmissions. First, the optimal scheduling policy is studied under different feedback mechanisms when the channel statistics are known; in particular, the standard automatic repeat request (ARQ) and hybrid ARQ (HARQ) protocols are considered. Then, for an unknown environment, an average-cost reinforcement learning (RL) algorithm is proposed that learns the system parameters and the transmission policy in real time. The effectiveness of the proposed methods are verified through numerical simulations.


2018 - Cache-Aided Content Delivery over Erasure Broadcast Channels [Articolo su rivista]
Mohammadi Amiri, M.; Gunduz, D.
abstract

A cache-aided broadcast network is studied, in which a server delivers contents to a group of receivers over a packet erasure broadcast channel. The receivers are divided into two sets with regards to their channel qualities: the weak and the strong receivers, where all the weak receivers have statistically worse channel qualities than all the strong receivers. The weak receivers, in order to compensate for the high erasure probability they encounter over the channel, are equipped with cache memories of equal size, while the receivers in the strong set have no caches. Data can be pre-delivered to the weak receivers' caches over the off-peak traffic period before the receivers reveal their demands. Allowing arbitrary erasure probabilities for the weak and strong receivers, a joint caching and channel coding scheme, which divides each file into several subfiles, and applies a different caching and delivery scheme for each subfile, is proposed. It is shown that all the receivers, even those without any cache memories, benefit from the presence of caches across the network. An information theoretic tradeoff between the cache size and the achievable rate is formulated. It is shown that the proposed scheme improves upon the state-of-The-art in terms of the achievable tradeoff.


2018 - Cache-Aided Interactive Multiview Video Streaming in Small Cell Wireless Networks [Relazione in Atti di Convegno]
Bourtsoulatze, E.; Gunduz, D.
abstract

The emergence of interactive multimedia applications with high data rate and low latency requirements has led to a drastic increase in the video data traffic over wireless cellular networks. Locally caching some of the contents at the small base stations of a macro-cell is a promising technology to cope with the increasing pressure on the backhaul connections, and to reduce the delay for demanding video applications. In this work, delivery of an interactive multiview video over an heterogeneous cellular network is studied. Differently from existing works that ignore the video characteristics, the caching and scheduling policies are jointly optimized, taking into account the quality of the delivered video and the video delivery time constraints. We formulate our joint caching and scheduling problem via submodular set function maximization and propose efficient greedy approaches to find a well performing joint caching and scheduling policy. Numerical evaluations show that our solution significantly outperforms benchmark algorithms based on popularity caching and independent scheduling.


2018 - Cache-aided fog radio access networks with partial connectivity [Relazione in Atti di Convegno]
Elkordy, A.; Motahari, A.; Nafie, M.; Gunduz, D.
abstract

Centralized coded caching and delivery is studied for a partially-connected fog radio access network (F-RAN), whereby a set of H edge nodes (ENs) (without caches), connected to a cloud server via orthogonal fronthaul links, serve K users over the wireless edge. The cloud server is assumed to hold a library of N files, each of size F bits; and each user, equipped with a cache of size MF bits, is connected to a distinct set of r ENs; or equivalently, the wireless edge from the ENs to the users is modeled as a partial interference channel. The objective is to minimize the normalized delivery time (NDT), which refers to the worst case delivery latency, when each user requests a single file from the library. An achievable coded caching and transmission scheme is proposed, which utilizes maximum distance separable (MDS) codes in the placement phase, and real interference alignment (IA) in the delivery phase, and its achievable NDT is presented for r = 2 and arbitrary cache size M, and also for arbitrary values of r when the cache capacity is sufficiently large.


2018 - Caching and coded delivery over Gaussian broadcast channels for energy efficiency [Articolo su rivista]
Mohammadi Amiri, M.; Gunduz, D.
abstract

A cache-aided K -user Gaussian broadcast channel is considered. The transmitter has a library of N equal-rate files, from which each user demands one. The impact of the equal-capacity receiver cache memories on the minimum required transmit power to satisfy all user demands is studied. Considering uniformly random demands across the library, both the minimum average power (averaged over all demand combinations) and the minimum peak power (minimum power required to satisfy all demand combinations) are studied. Upper bounds are presented on the minimum required average and peak transmit power as a function of the cache capacity considering both centralized and decentralized caching. The lower bounds on the minimum required average and peak power values are also derived assuming uncoded cache placement. The bounds for both the peak and average power values are shown to be tight in the centralized scenario through numerical simulations. The results in this paper show that proactive caching and coded delivery can provide significant energy savings in wireless networks.


2018 - Caching with Time-Varying Popularity Profiles: A Learning-Theoretic Perspective [Articolo su rivista]
Bharath, B. N.; Nagananda, K. G.; Gunduz, D.; Poor, H. V.
abstract

Content caching at the small-cell base stations (sBSs) in a heterogeneous wireless network is considered. A cost function is proposed that captures the backhaul link load, called the 'offloading loss,' which measures the fraction of the requested files that are not available in the sBS caches. As opposed to the previous approaches that consider time-invariant and perfectly known popularity profiles, caching with non-stationary and statistically dependent popularity profiles (assumed unknown, and hence, estimated) is studied from a learning-theoretic perspective. A probably approximately correct result is derived, which presents a high probability bound on the offloading loss difference, i.e., the error between the estimated and the optimal offloading loss. The difference is a function of the Rademacher complexity, the eta -mixing coefficient, the number of time slots, and a measure of discrepancy between the estimated and true popularity profiles. A cache update algorithm is proposed, and simulation results are presented to show its superiority over periodic updates. The performance analyses for Bernoulli and Poisson request models are also presented.


2018 - Centralized caching and delivery of correlated contents over a Gaussian broadcast channel [Relazione in Atti di Convegno]
Yang, Q.; Hassanzadeh, P.; Gunduz, D.; Erkip, E.
abstract

Content delivery in a multi-user cache-aided broadcast network is studied, where a server holding a database of correlated contents communicates with the users over a Gaussian broadcast channel (BC). The minimum transmission power required to satisfy all possible demand combinations is studied, when the users are equipped with caches of equal size. A lower bound on the required transmit power is derived, assuming uncoded cache placement, as a function of the cache capacity. A centralized joint cache and channel coding scheme is proposed, which not only utilizes the user's local caches, but also exploits the correlation among the contents in the database. This scheme provides an upper bound on the minimum required transmit power for a given cache capacity. Our results indicate that exploiting the correlations among the contents in a cache-aided Gaussian BC can provide significant energy savings.


2018 - Channel Sensing and Communication over a Time-Correlated Channel with an Energy Harvesting Transmitter [Articolo su rivista]
Abad, M. S. H.; Ercetin, O.; Gunduz, D.
abstract

An energy harvesting (EH) transmitter communicating over a time-correlated wireless channel is considered. The transmitter is capable of sensing the current channel state, albeit at the cost of both energy and transmission time. The EH transmitter aims to maximize its long-term throughput by choosing one of the following actions: 1) defer its transmission to save energy for future use; 2) transmit reliably at a low rate; 3) transmit at a high rate; and 4) sense the channel to reveal the channel state at a cost of energy and transmission time, and then decide to defer or to transmit. The problem is formulated as a partially observable Markov decision process with a belief on the channel state. The optimal policy is shown to exhibit a threshold behavior on the belief state, with battery-dependent threshold values. The optimal threshold values and performance are characterized numerically via the value iteration algorithm as well as a policy search algorithm that exploits the threshold structure of the optimal policy. Our results demonstrate that, despite the associated time and energy cost, sensing the channel intelligently to track the channel state improves the achievable long-term throughput significantly as compared to the performance of those protocols lacking this ability as well as the one that always senses the channel.


2018 - Coded Caching and Content Delivery with Heterogeneous Distortion Requirements [Articolo su rivista]
Yang, Q.; Gunduz, D.
abstract

Cache-aided coded content delivery is studied for devices with diverse quality-of-service requirements, specified by a different average distortion target. The network consists of a server holding a database of independent contents, and users equipped with local caches of different capacities. User caches are filled by the server during a low traffic period without the knowledge of particular user demands. As opposed to the current literature, which assumes that the users request files in their entirety, it is assumed that the users in the system have distinct distortion requirements; and therefore, each user requests a single file from the database to be served at a different distortion level. Our goal in this paper is to characterize the minimum delivery rate the server needs to transmit over an error-free shared link to satisfy all possible demand combinations at the requested distortion levels, considering both centralized and decentralized cache placement. For centralized cache placement, the optimal delivery rate is characterized for the two-file two-user scenario for any pair of target distortion requirements, when the underlying source distribution is successively refinable. For the two-user scenario with more than two successively refinable files, the optimal scheme is characterized when the cache capacities of the users are the same and the number of files is a multiple of 3. For the general source distribution, not necessarily successively refinable, and with arbitrary number of users and files, a layered caching and delivery scheme is proposed, assuming that scalable source coding is employed at the server. This allows dividing the problem into two subproblems: the lossless caching of each layer with heterogeneous cache sizes, and cache allocation among layers. A delivery rate minimization problem is formulated and solved numerically for each layer; while two different schemes are proposed to allocate user caches among layers, namely, proportional cache allocation and ordered cache allocation. A decentralized lossy coded caching scheme is also proposed, and its delivery rate performance is studied. Simulation results validate the effectiveness of the proposed schemes in both settings.


2018 - Coded Caching with Heterogeneous Cache Sizes and Link Qualities: The Two-User Case [Relazione in Atti di Convegno]
Cao, D.; Zhang, D.; Chen, P.; Liu, N.; Kang, W.; Gunduz, D.
abstract

The centralized coded caching problem is studied under heterogeneous cache sizes and channel qualities from the server to the users, focusing on the two-user case. A server holding N files is considered to be serving two users with arbitrary cache capacities of M-{1} and M-{2}, and it is assumed that in addition to a shared common link, each user also has a private link from the server available during the delivery phase. Optimal caching and delivery strategies that minimize the worst-case delivery latency are presented for an arbitrary N. The converse proof benefits from Tian's observation that it suffices to consider file-index symmetric caching schemes, while the achievability is obtained through memory-sharing among certain special (M-{1}, M-{2}) pairs. The optimal scheme is shown to exploit the private link capacities by transmitting part of the corresponding user's request in an uncoded fashion. When there are no private links, the results presented here improve upon the two known results in the literature, namely, i) equal cache capacities and arbitrary number of files; and ii) unequal cache capacities and N = 2 files.


2018 - Delay-Aware Coded Caching for Mobile Users [Relazione in Atti di Convegno]
Ozfatura, E.; Rarris, T.; Gunduz, D.; Ercetin, O.
abstract

Cache capacity-delay trade-off is studied for cooperative coded caching among small-cell base stations (SBSs) considering mobile users. First, a delay-aware coded caching policy is introduced, taking into account the popularity of the files and the maximum re-buffering delay constraint, which minimizes the average re-buffering delay of a mobile user under a given cache capacity constraint. Subsequently, a given average re-buffering delay constraint is considered to ensure a certain quality-of-service (QoS) target, and certain files are served by the macro-cell base station (MBS) when the cache capacity of the SBSs is not sufficient to store all the files in the library. A coded caching policy that minimizes the average amount of data served by the MBS is proposed for the latter scenario.


2018 - Energy-Optimal Control in Mobile Aerial Relay-Assisted Networks [Relazione in Atti di Convegno]
Faqir, O. J.; Gunduz, D.; Kerrigan, E. C.
abstract

Robotic networks, particularly of unmanned aerial vehicles (UAVs), are benefiting from increased on-board computing capabilities. The aim of our work is to minimize the total communication energy required by a UAV-assisted network to achieve certain mobility and data throughput objectives. We capture the full cost of communication by defining communication energy as the sum of transmission energy and propulsion energy used for the purpose of facilitating transmission. Simulation results show how joint optimization of mobility and transmission schemes results in significant energy savings and increased network capacity.


2018 - Energy-efficient communication in mobile aerial relay-assisted networks using predictive control [Relazione in Atti di Convegno]
Faqir, O. J.; Nie, Y.; Kerrigan, E. C.; Gunduz, D.
abstract

Energy-efficient communication in wireless networks of mobile autonomous agents mandates joint optimization of both transmission and propulsion energy. In Faqir et al. (2017) we developed communication-theoretic data transmission and Newtonian flight mechanics models to formulate a nonlinear optimal control problem. Here we extend the previous work by generalizing the communication model to include UAV-appropriate slow fading channels and specifically investigate the potential from joint optimization of mobility and communication over a multiple access channel. Numerical results exemplify the potential energy savings available to all nodes through this joint optimization. Finally, using the slow fading channel problem formulation, we generate a chance-constrained nonlinear model predictive control scheme for control of a terrestrial network served by a single UAV relay. Closed-loop simulations are performed subject to uncertainties in both transmission and mobility models.


2018 - Fundamental limits of latency in a cache-aided 4×4 interference channel [Relazione in Atti di Convegno]
Pujol Roig, J.; Motahari, A.; Tosato, F.; Gunduz, D.
abstract

Fundamental limits of communication is studied in a 4 × 4 interference network, in which the transmitters are equipped with cache memories. Each of the receivers requests one file from a library of N equal-size files. The caches at the transmitters are filled without the knowledge of the user demands, such that all possible demand combinations can be satisfied reliably over the interference channel. The achievable normalized delivery time (NDT) is studied under centralized cache placement. By combining the interference alignment (IA) and zero-forcing (ZF) techniques, a novel caching and transmission scheme is presented, and is shown to be optimal for all possible cache sizes; fully characterizing the NDT for the 4× 4 interference network with caches at the transmitter side.


2018 - Gaussian multiple access channels with one-bit quantizer at the receiver [Articolo su rivista]
Rassouli, B.; Varasteh, M.; Gunduz, D.
abstract

The capacity region of a two-transmitter Gaussian multiple access channel (MAC) under average input power constraints is studied, when the receiver employs a zero-threshold one-bit analogue-to-digital converter (ADC). It is proven that the input distributions of the two transmitters that achieve the boundary points of the capacity region are discrete. Based on the position of a boundary point, upper bounds on the number of the mass points of the corresponding distributions are derived. Furthermore, a lower bound on the sum capacity is proposed that can be achieved by time division with power control. Finally, inspired by the numerical results, the proposed lower bound is conjectured to be tight.


2018 - Information Transmission Bounds in Mobile Communication Networks [Relazione in Atti di Convegno]
Faqir, O. J.; Gunduz, D.; Kerrigan, E. C.
abstract

Networks of autonomous agents are becoming ubiquitous, motivating the challenging task of developing control policies for communication across these networks. The aim is usually to maximize the data transmission rate, or to reliably transfer a minimum amount of data subject to network constraints. For a stationary transmitter-receiver pair under an average transmit power constraint, the total amount of data that can be transmitted is unbounded as transmission time tends to infinity. We show that, in contrast, if the transmitter is moving at a constant speed, then the maximum amount of data that can be transmitted is bounded. This bound is of particular relevance to networks of aerial vehicles, where distances may quickly grow large and channel gain is dominated by path loss dynamics.


2018 - Joint optimization of transmission and propulsion in aerial communication networks [Relazione in Atti di Convegno]
Faqir, O.; Kerrigan, E.; Gunduz, D.
abstract

Communication energy in a wireless network of mobile autonomous agents should be considered as the sum of transmission energy and propulsion energy used to facilitate the transfer of information. Accordingly, communication-theoretic and Newtonian dynamic models are developed to model the communication and locomotion expenditures of each node. These are subsequently used to formulate a novel nonlinear optimal control problem (OCP) over a network of autonomous nodes. It is then shown that, under certain conditions, the OCP can be transformed into an equivalent convex form. Numerical results for a single link between a node and access point allow for comparison with known solutions before the framework is applied to a multiple-node UAV network, for which previous results are not readily extended. Simulations show that transmission energy can be of the same order of magnitude as propulsion energy allowing for possible savings, whilst also exemplifying how speed adaptations together with power control may increase the network throughput.


2018 - Lossy Coding of Correlated Sources Over a Multiple Access Channel: Necessary Conditions and Separation Results [Articolo su rivista]
Guler, B.; Gunduz, D.; Yener, A.
abstract

Lossy coding of correlated sources over a multiple access channel (MAC) is studied. First, a joint source-channel coding scheme is presented when the decoder has correlated side information. Next, the optimality of separate source and channel coding that emerges from the availability of a common observation at the encoders or side information at the encoders and the decoder is investigated. It is shown that separation is optimal when the encoders have access to a common observation whose lossless recovery is required at the decoder, and the two sources are independent conditioned on this common observation. Optimality of separation is also proved when the encoder and the decoder have access to shared side information conditioned on which the two sources are independent. These separation results obtained in the presence of side information are then utilized to provide a set of necessary conditions for the transmission of correlated sources over a MAC without side information. Finally, by specializing the obtained necessary conditions to the transmission of binary and Gaussian sources over a MAC, it is shown that they can potentially be tighter than the existing results in the literature, providing a novel converse for this fundamental problem.


2018 - Mobility and Popularity-Aware Coded Small-Cell Caching [Articolo su rivista]
Ozfatura, E.; Gunduz, D.
abstract

In heterogeneous cellular networks with caching capability, due to mobility of users and storage constraints of small-cell base stations (SBSs), users may not be able to download all of their requested content from the SBSs within the delay deadline of the content. In that case, the users are directed to the macro-cell base station (MBS) in order to satisfy the service quality requirement. Coded caching is exploited here to minimize the amount of data downloaded from the MBS, taking into account the mobility of the users as well as the popularity of the contents. An optimal distributed caching policy is presented when the delay deadline is below a certain threshold, and a distributed greedy caching policy is proposed when the delay deadline is relaxed.


2018 - On Perfect Privacy [Relazione in Atti di Convegno]
Rassouli, B.; Gunduz, D.
abstract

For a pair of (dependent) random variables (X, Y), the following problem is addressed: What is the maximum information that can be revealed about Y, while disclosing no information about X? Assuming that a Markov kernel maps Y to the revealed information U, it is shown that the maximum mutual information between Y and U, i.e., I(Y; U), can be obtained as the solution of a standard linear program, when X and U are required to be independent, called perfect privacy. The resulting quantity is shown to be greater than or equal to the non-private information about X carried by Y. For jointly Gaussian (X, Y), it is shown that perfect privacy is not possible if the kernel is applied to only Y; whereas perfect privacy can be achieved if the mapping is from both X and Y; that is, if the private variables can also be observed at the encoder. Finally, it is shown that when Y is not a deterministic function of X, perfect privacy is always feasible when the mapping has access to both X and Y.1


2018 - On the Capacity Region of a Cache-Aided Gaussian Broadcast Channel with Multi-Layer Messages [Relazione in Atti di Convegno]
Mohammadi Amiri, M.; Gunduz, D.
abstract

A cache-aided K-user Gaussian broadcast channel (BC) is studied. The transmitter has a library of N files, from which each user requests one. The users are equipped with caches of different sizes, which are filled without the knowledge of the user requests in a centralized manner. Differently from the literature, it is assumed that each file can be delivered to different users at different rates, which may correspond to different quality representations of the underlying content, e.g., scalable coded video segments. Accordingly, instead of a single achievable rate, the system performance is characterized by a rate tuple, which corresponds to the vector of rates users' requests can be delivered at. The goal is to characterize the set of all achievable rate tuples for a given total cache capacity by designing joint cache and channel coding schemes together with cache allocation across users. Assuming that the users are ordered in increasing channel quality, each file is coded into K layers, and only the first k layers of the requested file are delivered to user k, k=1, ldots, K. Three different coding schemes are proposed, which differ in the way they deliver the coded contents over the BC; in particular, time-division, superposition, and dirty paper coding schemes are studied. Corresponding achievable rate regions are characterized, and compared with a novel outer bound. To the best of our knowledge, this is the first work studying the delivery of files at different rates over a cache-aided noisy BC.


2018 - On the conditional entropy of wireless networks [Relazione in Atti di Convegno]
Coon, J. P.; Badiu, M.; Gunduz, D.
abstract

The characterization of topological uncertainty in wireless networks using the formalism of graph entropy has received interest in the spatial networks community. In this paper, we develop lower bounds on the entropy of a wireless network by conditioning on potential network observables. Two approaches are considered: 1) conditioning on subgraphs, and 2) conditioning on node positions. The first approach is shown to yield a relatively tight bound on the network entropy. The second yields a loose bound, in general, but it provides insight into the dependence between node positions (modelled using a homogenous binomial point process in this work) and the network topology.


2018 - Optimal demand-side management for joint privacy-cost optimization with energy storage [Relazione in Atti di Convegno]
Giulio, Giaconi; Gunduz, Deniz; Vincent Poor, H.
abstract

The smart meter (SM) privacy problem is addressed together with the cost of energy for the user. It is assumed that a storage device, e.g., an electrical battery, is available to the user, which can be utilized both to achieve privacy and to reduce the energy cost by modifying the energy consumption profile. Privacy is measured via the mean squared-error between the SM readings, which are reported to the utility provider (UP), and a target load; while time-of-use pricing is considered for energy cost calculation. The optimal trade-off between the achievable privacy and the energy cost is characterized by taking into account the limited capacity of the battery as well as the capability to sell energy to the UP. Extensive numerical simulations are presented to evaluate the performance of the proposed strategy for different system settings.


2018 - Polar Codes and Polar Lattices for the Heegard-Berger Problem [Articolo su rivista]
Shi, J.; Liu, L.; Gunduz, D.; Ling, C.
abstract

Explicit coding schemes are proposed to achieve the rate-distortion function of the Heegard-Berger problem using polar codes. Specifically, a nested polar code construction is employed to achieve the rate-distortion function for doubly symmetric binary sources when the side information may be absent. The nested structure contains two optimal polar codes for lossy source coding and channel coding, respectively. Moreover, a similar nested polar lattice construction is employed when the source and the side information are jointly Gaussian. The proposed polar lattice is constructed by nesting a quantization polar lattice and a capacity-achieving polar lattice for the additive white Gaussian noise channel.


2018 - Polar codes and polar lattices for the heegard-berger problem [Relazione in Atti di Convegno]
Shi, J.; Liu, L.; Gunduz, D.; Ling, C.
abstract

Explicit coding schemes are proposed to achieve the rate-distortion bound for the Heegard-Berger problem using polar codes. Specifically, a nested polar code construction is employed to achieve the rate-distortion bound for the binary case. The nested structure contains two optimal polar codes for lossy source coding and channel coding, respectively. Moreover, a similar nested polar lattice construction is employed for the Gaussian case. The proposed polar lattice is constructed by nesting a quantization polar lattice and an AWGN capacityachieving polar lattice.


2018 - Privacy-Aware Smart Metering: Progress and Challenges [Articolo su rivista]
Giaconi, G.; Gunduz, D.; Poor, H. V.
abstract

The next-generation energy network, the so-called smart grid (SG), promises tremendous increases in efficiency, safety, and flexibility in managing the electricity grid as compared to the legacy energy network. This is needed today more than ever, as global energy consumption is growing at an unprecedented rate and renewable energy sources (RESs) must be seamlessly integrated into the grid to assure a sustainable human development.


2018 - Reinforcement Learning for Proactive Caching of Contents with Different Demand Probabilities [Relazione in Atti di Convegno]
Somuyiwa, S.; Gunduz, D.; Gyorgy, A.
abstract

A mobile user randomly accessing a dynamic content library over a wireless channel is considered. At each time instant, a random number of contents are added to the library and each content remains relevant to the user for a random period of time. Contents are classified into finitely many classes such that whenever the user accesses the system, he requests each content randomly with a class-specific demand probability. Contents are downloaded to the user equipment (UE) through a wireless link whose quality also varies randomly with time. The UE has a cache memory of finite capacity, which can be used to proactively store contents before they are requested by the user. Any time contents are downloaded, the system incurs a cost (energy, bandwidth, etc.) that depends on the channel state at the time of download, and scales linearly with the number of contents downloaded. Our goal is to minimize the expected long-term average cost. The problem is modeled as a Markov decision process, and the optimal policy is shown to exhibit a threshold structure; however, since finding the optimal policy is computationally infeasible, parametric approximations to the optimal policy are considered, whose parameters are optimized using the policy gradient method. Numerical simulations show that the performance gain of the resulting scheme over traditional reactive content delivery is significant, and increases with the cache capacity. Comparisons with two performance lower bounds, one computed based on infinite cache capacity and another based on non-casual knowledge of the user access times and content requests, demonstrate that our scheme can perform close to the theoretical optimum.


2018 - Smart Meter Privacy with Renewable Energy and an Energy Storage Device [Articolo su rivista]
Giaconi, G.; Gunduz, D.; Poor, H. V.
abstract

A smart meter (SM) measures a consumer's electricity consumption and reports it automatically to a utility provider (UP) in almost real time. Despite many advantages of SMs, their use also leads to serious concerns about consumer privacy. In this paper, SM privacy is studied by considering the presence of a renewable energy source (RES) and a rechargeable battery (RB), which can be used to partially hide the consumer's energy consumption behavior. Privacy is measured by the information leakage rate, which denotes the average mutual information between the user's real energy consumption and the energy requested from the grid, which the SM reads and reports to the UP. The impact of the knowledge of the amount of energy generated by the RES at the UP is also considered. The minimum information leakage rate is characterized as a computable information theoretic single-letter expression in the two extreme cases, that is, when the battery capacity is infinite or zero. Numerical results are presented for the finite battery capacity case to illustrate the potential privacy gains from the existence of an RB. It is shown that, while the information leakage rate decreases with increasing availability of an RES, larger storage capacity is needed to fully exploit the available energy to improve the privacy.


2018 - Social learning for resilient data fusion against data falsification attacks [Articolo su rivista]
Rosas, F.; Chen, K. -C.; Gunduz, D.
abstract

Background: Internet of Things (IoT) suffers from vulnerable sensor nodes, which are likely to endure data falsification attacks following physical or cyber capture. Moreover, centralized decision-making and data fusion turn decision points into single points of failure, which are likely to be exploited by smart attackers. Methods: To tackle this serious security threat, we propose a novel scheme for enabling distributed decision-making and data aggregation through the whole network. Sensor nodes in our scheme act following social learning principles, resembling agents within a social network. Results: We analytically examine under which conditions local actions of individual agents can propagate through the network, clarifying the effect of Byzantine nodes that inject false information. Moreover, we show how our proposed algorithm can guarantee high network performance, even for cases when a significant portion of the nodes have been compromised by an adversary. Conclusions: Our results suggest that social learning principles are well suited for designing robust IoT sensor networks and enabling resilience against data falsification attacks.


2018 - SparseCast: Hybrid Digital-Analog Wireless Image Transmission Exploiting Frequency-Domain Sparsity [Articolo su rivista]
Tung, T-Z.; Gunduz, D.
abstract

A hybrid digital-analog wireless image transmission scheme, called SparseCast, is introduced, which provides graceful degradation with channel quality. SparseCast achieves improved end-to-end reconstruction quality while reducing the bandwidth requirement by exploiting frequency-domain sparsity through compressed sensing. The proposed algorithm produces a linear relationship between the channel signal-to-noise ratio and peak signal-to-noise ratio (PSNR) without requiring the channel state knowledge at the transmitter. This is particularly attractive when transmitting to multiple receivers or over unknown time-varying channels, as the receiver PSNR depends on the experienced channel quality and is not bottlenecked by the worst channel. SparseCast is benchmarked against two alternative algorithms: SoftCast and block CS-smooth projected Landweber (BCS-SPL). Our findings show that the proposed algorithm outperforms SoftCast by approximately 3.5 dB and BCS-SPL by 15.2 dB.


2018 - Testing Against Conditional Independence under Security Constraints [Relazione in Atti di Convegno]
Sreekumar, S.; Gunduz, D.
abstract

A distributed binary hypothesis testing problem involving three parties, a remote node, called the observer, a legitimate decoder, called the detector, and an adversary, is studied. The remote node observes a discrete memoryless source, and communicates its observations over a rate-limited noiseless public channel to the detector, which tests for the conditional independence of its own observations from that of the remote node, conditioned on some additional side information. The adversary, in addition to observing the public message, has access to its own correlated side-information. Considering the type 2 error exponent for a given type 1 error probability constraint as the performance measure for the hypothesis test at the detector, and equivocation of the source at the adversary as the secrecy measure, a single-letter characterization of the rate-error exponent-equivocation trade-off is established. Additionally, for a general distortion measure, imposing the average distortion at the adversary as the measure of secrecy achieved, an inner bound on the trade-off between the rate, error exponent and average distortion is obtained. This bound is shown to be tight under the less noisy condition on the adversary's side information.


2018 - The multi-layer information bottleneck problem [Relazione in Atti di Convegno]
Yang, Q.; Piantanida, P.; Gunduz, D.
abstract

The muti-layer information bottleneck (IB) problem, where information is propagated (or successively refined) from layer to layer, is considered. Based on information forwarded by the preceding layer, each stage of the network is required to preserve a certain level of relevance with regards to a specific hidden variable, quantified by the mutual information. The hidden variables and the source can be arbitrarily correlated. The optimal trade-off between rates of relevance and compression (or complexity) is obtained through a singleletter characterization, referred to as the rate-relevance region. Conditions of successive refinabilty are given. Binary source with BSC hidden variables and binary source with BSC/BEC mixed hidden variables are both proved to be successively refinable. We further extend our result to Guassian models. A counterexample of successive refinability is also provided.


2018 - Zero-delay source-channel coding with a low-resolution ADC front end [Articolo su rivista]
Varasteh, M.; Rassouli, B.; Simeone, O.; Gunduz, D.
abstract

Motivated by the practical constraints arising in emerging sensor network and Internet-of-Things (IoT) applications, the zero-delay transmission of a Gaussian measurement over a real single-input multiple-output (SIMO) additive white Gaussian noise (AWGN) channel is studied with a low-resolution analog-to-digital converter (ADC) front end. Joint optimization of the encoder and the decoder mapping is tackled under both the mean squared error (MSE) distortion and the distortion outage probability (DOP) criteria, with an average power constraint on the channel input. Optimal encoder and decoder mappings are identified for a one-bit ADC front end under both criteria. For the MSE distortion, the optimal encoder mapping is shown to be non-linear in general, while it tends to a linear encoder in the low signal-to-noise ratio (SNR) regime, and to an antipodal digital encoder in the high SNR regime. This is in contrast to the optimality of linear encoding at all SNR values in the presence of a full-precision front end. For the DOP criterion, it is shown that the optimal encoder mapping is piecewise constant and can take only two opposite values when it is non-zero. For both the MSE distortion and the DOP criteria, necessary optimality conditions are then derived for K-level ADC front ends as well as front ends with multiple one-bit ADCs. These conditions are used to obtain numerically optimized solutions. Extensive numerical results are also provided in order to gain insights into the structure of the optimal encoding and decoding mappings.


2017 - A low-complexity policy for outage probability minimization with an energy harvesting transmitter [Articolo su rivista]
Isikman, A. O.; Yuksel, M.; Gunduz, D.
abstract

Outage probability in an energy harvesting (EH) block-fading communication system is studied in the finite-horizon online setting. First, the offline version of the problem is considered, and formulated as a mixed integer linear program (MILP). Then, the infinite-horizon online problem (IIL) is considered relaxing the battery constraints. Solutions of these two problems provide lower bounds on the finite-horizon online problem, for which we provide a low-complexity heuristic scheme, called the fixed threshold transmission (FTT) scheme. Numerical results show that the FTT scheme achieves an outage performance close to the MILP lower bound for a wide range of operation regimes, and close to IIL when the EH rate is low. It is also observed that the power allocated by the FTT scheme resembles the optimal offline solution with high probability, despite the lack of information about future channel states and energy arrivals.


2017 - Cache-aided data delivery over erasure broadcast channels [Relazione in Atti di Convegno]
Mohammadi Amiri, M.; Gunduz, D.
abstract

A cache-aided erasure broadcast channel is studied. The receivers are divided into two sets: the weak and strong receivers, where the receivers in the same set all have the same erasure probability. The weak receivers, in order to compensate for the high erasure probability, are equipped with cache memories of equal size, while the receivers in the strong set have no caches. Data can be pre-delivered to weak receivers' caches over the off-peak traffic period before the receivers reveal their demands. A joint caching and channel coding scheme is proposed such that all the receivers, even the receivers without any cache memories, benefit from the presence of caches across the network. The trade-off between the cache size and the achievable rate is studied, and it is shown that the proposed scheme significantly improves the achievable trade-off upon the state-of-the-art.


2017 - Capacity region of a one-bit quantized Gaussian multiple access channel [Relazione in Atti di Convegno]
Rassouli, B.; Varasteh, M.; Gunduz, D.
abstract

The capacity region of a two-transmitter Gaussian multiple access channel (MAC) under average input power constraints is studied, when the receiver employs a zero-threshold one-bit analog-to-digital converter (ADC). It is proved that the input distributions that achieve the boundary points of the capacity region are discrete. Based on the position of a boundary point, upper bounds on the number of the mass points of the corresponding distributions are derived. Finally, a conjecture on the sufficiency of K mass points in a point-to-point real AWGN with a K-bin ADC front end (symmetric or asymmetric) is settled.1


2017 - Communication over a time correlated channel with an energy harvesting transmitter [Relazione in Atti di Convegno]
Abad, M.; Gunduz, D.; Ercetin, O.
abstract

In this work, communication over a time-correlated point-to-point wireless channel is studied for an energy harvesting (EH) transmitter. In this model, we take into account the time and energy cost of acquiring channel state information. At the beginning of the time slot, the EH transmitter, has to choose among three possible actions: i) deferring the transmission to save its energy for future use, ii) transmitting without sensing, and iii) sensing the channel before transmission. At each time slot, the transmitter chooses one of the three possible actions to maximize the total expected discounted number of bits transmitted over an infinite time horizon. This problem can be formulated as a partially observable Markov decision process (POMDP) which is then converted to an ordinary MDP by introducing a belief on the channel state, and the optimal policy is shown to exhibit a threshold behavior on the belief state, with battery-dependent threshold values. Optimal threshold values and corresponding optimal performance are characterized through numerical simulations, and it is shown that having the sensing action and intelligently using it to track the channel state improves the achievable long-term throughput significantly.


2017 - Decentralized Caching and Coded Delivery with Distinct Cache Capacities [Articolo su rivista]
Mohammadi Amiri, M.; Yang, Q.; Gunduz, D.
abstract

Decentralized proactive caching and coded delivery is studied in a content delivery network, where each user is equipped with a cache memory, not necessarily of equal capacity. Cache memories are filled in advance during the off-peak traffic period in a decentralized manner, i.e., without the knowledge of the number of active users, their identities, or their particular demands. User demands are revealed during the peak traffic period, and are served simultaneously through an error-free shared link. The goal is to find the minimum delivery rate during the peak traffic period that is sufficient to satisfy all possible demand combinations. A group-based decentralized caching and coded delivery scheme is proposed, and it is shown to improve upon the state of the art in terms of the minimum required delivery rate when there are more users in the system than files. Numerical results indicate that the improvement is more significant as the cache capacities of the users become more skewed. A new lower bound on the delivery rate is also presented, which provides a tighter bound than the classical cut-set bound.


2017 - Decentralized caching and coded delivery over Gaussian broadcast channels [Relazione in Atti di Convegno]
Mohammadi Amiri, M.; Gunduz, D.
abstract

A cache-aided K-user Gaussian broadcast channel (BC) is considered. The transmitter has a library of N equal-rate files, from which each user demands one. The impact of the equal-capacity receiver cache memories on the minimum required transmit power to satisfy all user demands is studied. Decentralized caching with uniformly random demands is considered, and both the minimum average power (averaged over all demand combinations) and the minimum peak power (minimum power required to satisfy the worst-case demand combination) are studied. Upper and lower bounds are presented on the minimum required average and peak transmit power as a function of the cache capacity, assuming uncoded cache placement. The gaps between the upper and lower bounds on both the minimum peak and average power values are shown to be relatively small through numerical results, particularly for large cache capacities.


2017 - Decentralized coded caching with distinct cache capacities [Relazione in Atti di Convegno]
Mohammadi Amiri, M.; Yang, Q.; Gunduz, D.
abstract

Decentralized coded caching is studied for a content server with N files, each of size F bits, serving K active users, each equipped with a cache of distinct capacity. It is assumed that the users' caches are filled in advance during the off-peak traffic period without the knowledge of the number of active users, their identities, or the particular demands. User demands are revealed during the peak traffic period, and are served simultaneously through an error-free shared link. A new decentralized coded caching scheme is proposed for this scenario, and it is shown to improve upon the state-of-the-art in terms of the required delivery rate over the shared link, when there are more users in the system than the number of files. Numerical results indicate that the improvement becomes more significant as the cache capacities of the users become more skewed.


2017 - Distributed hypothesis testing over noisy channels [Relazione in Atti di Convegno]
Sreekumar, S.; Gunduz, D.
abstract

A distributed binary hypothesis testing problem, in which multiple observers transmit their observations to a detector over noisy channels, is studied. Together with its own observations, the goal of the detector is to decide between two hypotheses for the joint distribution of the data. Single-letter upper and lower bounds on the optimal type 2 error exponent (T2-EE), when the type 1 error probability vanishes with the block-length are obtained. These bounds coincide and characterize the optimal T2-EE when only a single helper is involved. Our result shows that the optimal T2-EE depends on the marginal distributions of the data and the channels rather than their joint distribution. However, an operational separation between HT and channel coding does not hold, and the optimal T2-EE is achieved by generating channel inputs correlated with observed data.


2017 - Energy-Distortion Exponents in Lossy Transmission of Gaussian Sources Over Gaussian Channels [Articolo su rivista]
Koken, E.; Tuncel, E.; Gunduz, D.
abstract

Lossy transmission of Gaussian sources over energy-limited Gaussian point-to-point and broadcast channels is studied under the infinite bandwidth regime, i.e., when the number of channel uses is unlimited. Using previously known asymptotic achievability and converse results, the energy-distortion exponent, defined as the rate of decay of the square-error distortion as the available energy-to-noise ratio increases without bound, is completely characterized for both the point-to-point and broadcast channel cases. Turning then to the scenario of zero-delay transmission, where outage events with arbitrarily small probability are allowed, it is shown that the same energy-distortion exponent as in the infinite-delay case can be achieved in all the studied scenarios.


2017 - Energy-efficient wireless content delivery with proactive caching [Relazione in Atti di Convegno]
Somuyiwa, S.; Gyorgy, A.; Gunduz, D.
abstract

We propose an intelligent proactive content caching scheme to reduce the energy consumption in wireless downlink. We consider an online social network (OSN) setting where new contents are generated over time, and remain relevant to the user for a random lifetime. Contents are downloaded to the user equipment (UE) through a time-varying wireless channel at an energy cost that depends on the channel state and the number of contents downloaded. The user accesses the OSN at random time instants, and consumes all the relevant contents. To reduce the energy consumption, we propose proactive caching of contents under favorable channel conditions to a finite capacity cache memory. Assuming that the channel quality (or equivalently, the cost of downloading data) is memoryless over time slots, we show that the optimal caching policy, which may replace contents in the cache with shorter remaining lifetime with contents at the server that remain relevant longer, has a threshold structure with respect to the channel quality. Since the optimal policy is computationally demanding in practice, we introduce a simplified caching scheme and optimize its parameters using policy search. We also present two lower bounds on the energy consumption. We demonstrate through numerical simulations that the proposed caching scheme significantly reduces the energy consumption compared to traditional reactive caching tools, and achieves close-to-optimal performance for a wide variety of system parameters.


2017 - Finite-length linear schemes for joint source-channel coding over Gaussian broadcast channels with feedback [Articolo su rivista]
Murin, Y.; Kaspi, Y.; Dabora, R.; Gunduz, D.
abstract

In this paper, we study linear encoding for a pair of correlated Gaussian sources transmitted over a two-user Gaussian broadcast channel in the presence of unit-delay noiseless feedback, abbreviated as the GBCF. Each pair of source samples is transmitted using a linear transmission scheme in a finite number of channel uses. We investigate three linear transmission schemes: A scheme based on the Ozarow-Leung (OL) code, a scheme based on the linear quadratic Gaussian (LQG) code of Ardestanizadeh et al., and a novel scheme derived in this paper using a dynamic programming (DP) approach. For the OL and LQG schemes we present lower and upper bounds on the minimal number of channel uses needed to achieve a target mean-square error (MSE) pair. For the LQG scheme in the symmetric setting, we identify the optimal scaling of the sources, which results in a significant improvement of its finite horizon performance, and, in addition, characterize the (exact) minimal number of channel uses required to achieve a target MSE. Finally, for the symmetric setting, we show that for any fixed and finite number of channel uses, the DP scheme achieves an MSE lower than the MSE achieved by either the LQG or the OL schemes.


2017 - Fundamental Limits of Coded Caching: Improved Delivery Rate-Cache Capacity Tradeoff [Articolo su rivista]
Mohammadi Amiri, M.; Gunduz, D.
abstract

A centralized coded caching system, consisting of a server delivering N popular files, each of size F bits, to K users through an error-free shared link, is considered. It is assumed that each user is equipped with a local cache memory with capacity MF bits, and contents can be proactively cached into these caches over a low traffic period, however, without the knowledge of the user demands. During the peak traffic period, each user requests a single file from the server. The goal is to minimize the number of bits delivered by the server over the shared link, known as the delivery rate, over all user demand combinations. A novel coded caching scheme for the cache capacity of M= (N-1)/K is proposed. It is shown that the proposed scheme achieves a smaller delivery rate than the existing coded caching schemes in the literature, when K > N ≥ 3. Furthermore, we argue that the delivery rate of the proposed scheme is within a constant multiplicative factor of 2 of the optimal delivery rate for cache capacities 1/K ≤ M ≤ (N-1)/K, when K > N ≥ 3.


2017 - Improved delivery rate-cache capacity trade-off for centralized coded caching [Relazione in Atti di Convegno]
Mohammadi Amiri, M.; Gunduz, D.
abstract

Centralized coded caching problem, in which a server with N distinct files, each with the size of F bits, serves K users, each equipped with a cache of capacity MF bits, is considered. The server is allowed to proactively cache contents into user terminals during the placement phase, without knowing the particular user requests. After the placement phase, each user requests one of the N files from the server, and all the users' requests are satisfied simultaneously by the server through an error-free shared link during the delivery phase. A novel coded caching algorithm is proposed, which is shown to achieve a smaller delivery rate compared to the existing coded caching schemes in the literature for a range of N and K values; particularly when the number of files is larger than the number of users in the system.


2017 - Improved policy representation and policy search for proactive content caching in wireless networks [Relazione in Atti di Convegno]
Somuyiwa, S.; Gyorgy, A.; Gunduz, D.
abstract

We study the problem of proactively pushing contents into a finite capacity cache memory of a user equipment in order to reduce the long-term average energy consumption in a wireless network. We consider an online social network (OSN) framework, in which new contents are generated over time and each content remains relevant to the user for a random time period, called the lifetime of the content. The user accesses the OSN through a wireless network at random time instants to download and consume all the relevant contents. Downloading contents has an energy cost that depends on the channel state and the number of downloaded contents. Our aim is to reduce the long-term average energy consumption by proactively caching contents at favorable channel conditions. In previous work, it was shown that the optimal caching policy is infeasible to compute (even with the complete knowledge of a stochastic model describing the system), and a simple family of threshold policies was introduced and optimised using the finite difference method. In this paper we improve upon both components of this approach: we use linear function approximation (LFA) to better approximate the considered family of caching policies, and apply the REINFORCE algorithm to optimise its parameters. Numerical simulations show that the new approach provides reduction in both the average energy cost and the running time for policy optimisation.


2017 - Interference networks with caches at both ends [Relazione in Atti di Convegno]
Pujol Roig, J.; Gunduz, D.; Tosato, F.
abstract

A Kt χ Kr cache-aided wireless interference network, in which both the transmitters and the receivers are equipped with cache memories is studied. Each user requests one file from a library of N popular files. The goal is to design the cache contents without the knowledge of the particular user demands, such that all possible demand combinations can be satisfied reliably over the interference channel. The achievable sum degrees-of-freedom (sDoF) and the normalized delivery time (NDT) are studied for centralized and decentralized network architectures, respectively. First, using a combination of interference alignment (IA), zero-forcing (ZF) and interference cancellation (IC) techniques, a novel caching and transmission scheme for centralized networks is introduced, and it is shown to improve the sDoF upon the state-of-the-art. Then, the NDT is studied when the content placement at the receiver caches is carried out in a decentralized manner. Our results indicate that, for this particular network architecture, caches located at the receiver side are more effective than those at the transmitter side in order to reduce the NDT.


2017 - On the energy-distortion tradeoff of Gaussian broadcast channels with feedback [Articolo su rivista]
Murin, Y.; Kaspi, Y.; Dabora, R.; Gunduz, D.
abstract

This work studies the relationship between the energy allocated for transmitting a pair of correlated Gaussian sources over a two-user Gaussian broadcast channel with noiseless channel output feedback (GBCF) and the resulting distortion at the receivers. Our goal is to characterize the minimum transmission energy required for broadcasting a pair of source samples, such that each source can be reconstructed at its respective receiver to within a target distortion, when the source-channel bandwidth ratio is not restricted. This minimum transmission energy is defined as the energy-distortion tradeoff (EDT). We derive a lower bound and three upper bounds on the optimal EDT. For the upper bounds, we analyze the EDT of three transmission schemes: two schemes are based on separate source-channel coding and apply encoding over multiple samples of source pairs, and the third scheme is a joint source-channel coding scheme that applies uncoded linear transmission on a single source-sample pair and is obtained by extending the Ozarow-Leung (OL) scheme. Numerical simulations show that the EDT of the OL-based scheme is close to that of the better of the two separation-based schemes, which makes the OL scheme attractive for energy-efficient, low-latency and low-complexity source transmission over GBCFs.


2017 - On the necessary conditions for transmitting correlated sources over a multiple access channel [Relazione in Atti di Convegno]
Guler, B.; Gunduz, D.; Yener, A.
abstract

We study the lossy communication of correlated sources over a multiple access channel (MAC). In particular, we provide a new set of necessary conditions for the achievability of a distortion pair over a given channel. The necessary conditions are then specialized to the case of bivariate Gaussian sources and doubly symmetric binary sources over a Gaussian multiple access channel. Our results indicate that the new necessary conditions provide the tightest conditions to date in certain cases.


2017 - Privacy-Cost Trade-offs in Demand-Side Management with Storage [Articolo su rivista]
Tan, O.; Gomez-Vilardebo, J.; Gunduz, D.
abstract

Demand-side energy management (EM) is studied from a privacy-cost trade-off perspective, considering time-of-use pricing and the presence of an energy storage unit. Privacy is measured as the variation of the power withdrawn from the grid from a fixed target value. Assuming non-causal knowledge of the household's aggregate power demand profile and the electricity prices at the energy management unit (EMU), the privacy-cost trade-off is formulated as a convex optimization problem, and a low-complexity backward water-filling algorithm is proposed to compute the optimal EM policy. The problem is studied also in the online setting assuming that the power demand profile is known to the EMU only causally, and the optimal EM policy is obtained numerically through dynamic programming (DP). Due to the high computational cost of DP, a low-complexity heuristic EM policy with a performance close to the optimal online solution is also proposed, exploiting the water-filling algorithm obtained in the offline setting. As an alternative, information theoretic leakage rate is also evaluated, and shown to follow a similar trend as the load variance, which supports the validity of the load variance as a measure of privacy. Finally, the privacy-cost trade-off, and the impact of the size of the storage unit on this trade-off are studied through numerical simulations using real smart meter data in both the offline and online settings.


2017 - Smart meter privacy based on adversarial hypothesis testing [Relazione in Atti di Convegno]
Li, Z.; Oechtering, T.; Gunduz, D.
abstract

Privacy-preserving energy management is studied in the presence of a renewable energy source. It is assumed that the energy demand/supply from the energy provider is tracked by a smart meter. The resulting privacy leakage is measured through the probabilities of error in a binary hypothesis test, which tries to detect the consumer behavior based on the meter readings. An optimal privacy-preserving energy management policy maximizes the minimal Type II probability of error subject to a constraint on the Type I probability of error. When the privacy-preserving energy management policy is based on all the available information of energy demands, energy supplies, and hypothesis, the asymptotic exponential decay rate of the maximum minimal Type II probability of error is characterized by a divergence rate expression. Two special privacy-preserving energy management policies, the memoryless hypothesis-aware policy and the hypothesis-unaware policy with memory, are then considered and their performances are compared. Further, it is shown that the energy supply alphabet can be constrained to the energy demand alphabet without loss of optimality for the evaluation of a single-letter-divergence privacy-preserving guarantee.


2017 - Zero-delay source-channel coding with a 1-Bit ADC front end and correlated receiver side information [Articolo su rivista]
Varasteh, M.; Rassouli, B.; Simeone, O.; Gunduz, D.
abstract

Zero-delay transmission of a Gaussian source over an additive white Gaussian noise (AWGN) channel is considered with a 1-bit analog-to-digital converter (ADC) front end and correlated side information at the receiver. The design of the optimal encoder and decoder is studied for two different performance criteria, namely the mean squared error (MSE) distortion and the distortion outage probability (DOP), under an average power constraint on the channel input. For both criteria, necessary optimality conditions for the encoder and the decoder are derived, which are then used to numerically obtain encoder and decoder mappings that satisfy these conditions. Using these conditions, it is observed that the numerically optimized encoder (NOE) under the MSE distortion criterion is periodic, and its period increases with the correlation between the source and the receiver side information. For the DOP, it is instead seen that the NOE mappings periodically acquire positive and negative values, which decay to zero with increasing source magnitude, and the interval over which the mapping takes non-zero values becomes wider with the correlation between the source and the side information. Finally, inspired by the mentioned properties of the NOE mappings, parameterized encoder mappings with a small number of degrees of freedom are proposed for both distortion criteria, and their performance is compared with that of the NOE mappings.


2016 - Capacity of a class of state-dependent orthogonal relay channels [Articolo su rivista]
Aguerri, I. E.; Gunduz, D.
abstract

The class of orthogonal relay channels in which the orthogonal channels connecting the source terminal to the relay and the destination, and the relay to the destination, depend on a state sequence, is considered. It is assumed that the state sequence is fully known at the destination, while it is not known at the source or the relay. The capacity of this class of relay channels is characterized, and shown to be achieved by the partial decode-compress-and-forward (pDCF) scheme. Then, the capacity of certain binary and Gaussian state-dependent orthogonal relay channels are studied in detail, and it is shown that the compress-and-forward (CF) and partial-decode-and-forward (pDF) schemes are suboptimal in general. To the best of our knowledge, this is the first single relay channel model for which the capacity is achieved by pDCF, while pDF and CF schemes are both suboptimal. Furthermore, it is shown that the capacity of the considered class of state-dependent orthogonal relay channels is in general below the cut-set bound. The conditions under which pDF or CF suffices to meet the cut-set bound, and hence, achieve the capacity, are also derived.


2016 - Centralized coded caching for heterogeneous lossy requests [Relazione in Atti di Convegno]
Yang, Q.; Gunduz, D.
abstract

Centralized coded caching of popular contents is studied for users with heterogeneous distortion requirements, corresponding to diverse processing and display capabilities of mobile devices. Users' distortion requirements are assumed to be fixed and known, while their particular demands are revealed only after the placement phase. Modeling each file in the database as an independent and identically distributed Gaussian vector, the minimum delivery rate that can satisfy any demand combination within the corresponding distortion target is studied. The optimal delivery rate is characterized for the special case of two users and two files for any pair of distortion requirements. For the general setting with multiple users and files, a layered caching and delivery scheme, which exploits the successive refinability of Gaussian sources, is proposed. This scheme caches each content in multiple layers, and it is optimized by solving two subproblems: lossless caching of each layer with heterogeneous cache capacities, and allocation of available caches among layers. The delivery rate minimization problem for each layer is solved numerically, while two schemes, called the proportional cache allocation (PCA) and ordered cache allocation (OCA), are proposed for cache allocation. These schemes are compared with each other and the cut-set bound through numerical simulations.


2016 - Coded caching for a large number of users [Relazione in Atti di Convegno]
Mohammadi Amiri, M.; Yang, Q.; Gunduz, D.
abstract

We consider the coded caching problem with a central server containing N files, each of length F bits, and K users, each equipped with a cache of capacity MF bits. We assume that coded contents can be proactively placed into users' caches at no cost during the placement phase. During the delivery phase, each user requests exactly one file from the database, and all the requests are served simultaneously by the server over an error-free common link. The goal is to utilize the local cache memories at the users to reduce the delivery rate from the server during the peak period. Here, we focus on a system which has more users than files, i.e., K > N. We first consider the centralized caching problem, in which the number and identity of active users are known in advance, and propose a group-based coded caching scheme for M = N/K, which improves upon the best achievable scheme in the literature. The proposed centralized caching scheme is then exploited in a decentralized setting, in which neither the number nor the identity of the active users are known during the placement phase. It is shown that the proposed coded caching scheme improves upon the best known decentralized delivery rate as well.


2016 - Distortion Exponent in MIMO Fading Channels with Time-Varying Source Side Information [Articolo su rivista]
Aguerri, I. E.; Gunduz, D.
abstract

Transmission of a Gaussian source over a time-varying multiple-input multiple-output (MIMO) channel is studied under strict delay constraints. Availability of a correlated side information at the receiver is assumed, whose quality, i.e., its correlation with the source signal, also varies over time. A block-fading model is considered for the states of the time-varying channel and side information; perfect state information at the receiver is assumed, while the transmitter knows only the statistics. The high signal to noise ratio performance, characterized by the distortion exponent, is studied for this joint source-channel coding problem. An upper bound is derived and compared with several lower bounds based on list decoding (LD), hybrid digital-analog transmission, as well as multi-layer schemes, which transmit successive refinements of the source, relying on progressive or superposition transmission with LD. The optimal distortion exponent is characterized for the single-input multiple-output and multiple-input single-output scenarios by showing that the distortion exponent achieved by multi-layer superposition encoding with joint decoding meets the proposed upper bound. In the MIMO scenario, the optimal distortion exponent is characterized in the low bandwidth ratio regime, and it is shown that the multi-layer superposition encoding performs very close to the upper bound in the high bandwidth ratio regime.


2016 - Energy harvesting wireless networks with correlated energy sources [Relazione in Atti di Convegno]
Abad, M.; Gunduz, D.; Ercetin, O.
abstract

This work considers a system with two energy harvesting (EH) nodes transmitting to a common destination over a random access channel. The amount of harvested energy is assumed to be random and independent over time, but correlated among the nodes possibly with respect to their relative position. A threshold-based transmission policy is developed for the maximization of the expected aggregate network throughput. Assuming that there is no a priori channel state or EH information available to the nodes, the aggregate network throughput is obtained. The optimal thresholds are determined for two practically important special cases: i) at any time only one of the sensors harvests energy due to, for example, physical separation of the nodes; ii) the nodes are spatially close, and at any time, either both nodes or none of them harvests energy.


2016 - Energy-distortion tradeoff for the Gaussian broadcast channel with feedback [Relazione in Atti di Convegno]
Murin, Y.; Kaspi, Y.; Dabora, R.; Gunduz, D.
abstract

This work focuses on the minimum transmission energy required for communicating a pair of correlated Gaussian sources over a two-user Gaussian broadcast channel with noiseless and causal channel output feedback (GBCF). We study the fundamental limit on the required transmission energy for broadcasting a pair of source samples, such that each source can be reconstructed at its respective receiver to within a target distortion, when the source-channel bandwidth ratio is not restricted. We derive a lower bound and three distinct upper bounds on the minimum required energy. For the upper bounds we analyze three transmission schemes: Two schemes are based on separate source-channel coding, and apply coding over multiple samples of source pairs. The third scheme is based on joint source-channel coding obtained by extending the Ozarow-Leung (OL) transmission scheme, which applies uncoded linear transmission. Numerical simulations show that despite its simplicity, the energy-distortion tradeoff of the OL-based scheme is close to that of the better separation-based scheme, which indicates that the OL scheme is attractive for energy-efficient source transmission over GBCFs.


2016 - Joint source-channel coding with one-bit ADC front end [Relazione in Atti di Convegno]
Varasteh, M.; Simeone, O.; Gunduz, D.
abstract

This paper considers the zero-delay transmission of a Gaussian source over an additive white Gaussian noise (AWGN) channel with a one-bit analog-to-digital converter (ADC) front end. The optimization of the encoder and decoder is tackled under both the mean squared error (MSE) distortion and the outage distortion criteria with an average power constraint. For MSE distortion, the optimal transceiver is identified over the space of symmetric encoders. This result demonstrates that the linear encoder, which is optimal with a full-precision front end, approaches optimality only in the low signal-to-noise ratio (SNR) regime; while, digital transmission is optimal in the high SNR regime. For the outage distortion criterion, the structure of the optimal encoder and decoder are obtained. In particular, it is shown that the encoder mapping is piecewise constant and can take only two opposite values when it is non-zero.


2016 - Joint source-channel coding with time-varying channel and side-information [Articolo su rivista]
Aguerri, I. E.; Gunduz, D.
abstract

Transmission of a Gaussian source over a time-varying Gaussian channel is studied in the presence of time-varying correlated side information at the receiver. A block fading model is considered for both the channel and the side information, whose states are assumed to be known only at the receiver. The optimality of separate source and channel coding in terms of average end-to-end distortion is shown when the channel is static, while the side information state follows a discrete or a continuous and quasiconcave distribution. When both the channel and side information states are timevarying, separate source and channel coding is suboptimal in general. A partially informed encoder lower bound is studied by providing the channel state information to the encoder. Several achievable transmission schemes are proposed based on uncoded transmission, separate source and channel coding, joint decoding, and hybrid digital-analog transmission. Uncoded transmission is shown to be optimal for a class of continuous and quasiconcave side information state distributions, while the channel gain may have an arbitrary distribution. To the best of our knowledge, this is the first example, in which the uncoded transmission achieves the optimal performance thanks to the time-varying nature of the states, while it is suboptimal in the static version of the same problem. Then, the optimal distortion exponent, which quantifies the exponential decay rate of the expected distortion in the high SNR regime, is characterized for Nakagami distributed channel and side information states, and it is shown to be achieved by hybrid digital-analog and joint decoding schemes in certain cases, illustrating the suboptimality of pure digital or analog transmission in general.


2016 - Linear Transmission of Composite Gaussian Measurements over a Fading Channel under Delay Constraints [Articolo su rivista]
Tan, O.; Gunduz, D.; Gomez-Vilardebo, J.
abstract

Delay constrained linear transmission (LT) strategies are considered for the transmission of composite Gaussian measurements over an additive white Gaussian noise fading channel under an average power constraint. If the channel state information (CSI) is known by both the encoder and decoder, the optimal LT scheme in terms of the average mean-square error distortion is characterized under a strict delay constraint, and a graphical interpretation of the optimal power allocation strategy is presented. Then, for general delay constraints, two LT strategies are proposed based on the solution to a particular multiple measurements-parallel channels scenario. It is shown that the distortion decreases as the delay constraint is relaxed, and when the delay constraint is completely removed, both strategies achieve the optimal performance under certain matching conditions. If the CSI is known only by the decoder, the optimal LT strategy is derived under a strict delay constraint. The extension to general delay constraints is elusive. As a first step toward understanding the structure of the optimal scheme in this case, it is shown that for the multiple measurements-parallel channels scenario, any LT scheme that uses only a one-to-one linear mapping between measurements and channels is suboptimal in general.


2016 - Non-orthogonal unicast and broadcast transmission via joint beamforming and LDM in cellular networks [Relazione in Atti di Convegno]
Zhao, J.; Simeone, O.; Gunduz, D.; Gomez-Barquero, D.
abstract

Research efforts to incorporate multicast and broadcast transmission into the cellular network architecture are gaining momentum, particularly for multimedia streaming applications. Layered division multiplexing (LDM), a form of nonorthogonal multiple access (NOMA), can potentially improve unicast throughput and broadcast coverage with respect to traditional orthogonal frequency division multiplexing (FDM) or time division multiplexing (TDM), by simultaneously using the same frequency and time resources for multiple unicast or broadcast transmissions. In this paper, the performance of LDM-based unicast and broadcast transmission in a cellular network is studied by assuming a single frequency network (SFN) operation for the broadcast layer, while allowing for arbitrarily clustered cooperation for the transmission of unicast data streams. Beamforming and power allocation between unicast and broadcast layers, and hence the so-called injection level in the LDM literature, are optimized with the aim of minimizing the sum-power under constraints on the user-specific unicast rates and on the common broadcast rate. The problem is tackled by means of successive convex approximation (SCA) techniques, as well as through the calculation of performance upper bounds by means of semidefinite relaxation (SDR). Numerical results are provided to compare the orthogonal and non-orthogonal multiplexing of broadcast and unicast traffic.


2016 - On lossy transmission of correlated sources over a multiple access channel [Relazione in Atti di Convegno]
Güler, B.; Gunduz, D.; Yener, A.
abstract

We study lossy communication of correlated sources over a multiple access channel. In particular, we provide a joint source-channel coding scheme for transmitting correlated sources with decoder side information, and study the conditions under which separate source and channel coding is optimal. For the latter, the encoders and/or the decoder have access to a common observation conditioned on which the two sources are independent. By establishing necessary and sufficient conditions, we show the optimality of separation when the encoders and the decoder both have access to the common observation. We also demonstrate that separation is optimal when only the encoders have access to the common observation whose lossless recovery is required at the decoder. As a special case, we study separation for sources with a common part. Our results indicate that side information can have significant impact on the optimality of source-channel separation in lossy transmission.


2016 - Smart meter privacy with renewable energy and a finite capacity battery [Relazione in Atti di Convegno]
Giaconi, G.; Gunduz, D.
abstract

We address the smart meter (SM) privacy problem by considering the availability of a renewable energy source (RES) and a battery which can be exploited by a consumer to partially hide the consumption pattern from the utility provider (UP). Privacy is measured by the mutual information rate between the consumer's energy consumption and the renewable energy generation process, and the energy received from the grid, where the latter is known by the UP through the SM readings, and the former two are to be kept private. By expressing the information leakage as an additive quantity, we cast the problem as a stochastic control problem, and formulate the corresponding Bellman equations.


2016 - Wireless content caching for small cell and D2D networks [Articolo su rivista]
Gregori, M.; Gomez-Vilardebo, J.; Matamoros, J.; Gunduz, D.
abstract

The fifth generation wireless networks must provide fast and reliable connectivity while coping with the ongoing traffic growth. It is of paramount importance that the required resources, such as energy and bandwidth, do not scale with traffic. While the aggregate network traffic is growing at an unprecedented rate, users tend to request the same popular contents at different time instants. Therefore, caching the most popular contents at the network edge is a promising solution to reduce the traffic and the energy consumption over the backhaul links. In this paper, two scenarios are considered, where caching is performed either at a small base station, or directly at the user terminals, which communicate using Device-to-Device (D2D) communications. In both scenarios, joint design of the transmission and caching policies is studied when the user demands are known in advance. This joint design offers two different caching gains, namely, the pre-downloading and local caching gains. It is shown that the finite cache capacity limits the attainable gains, and creates an inherent tradeoff between the two types of gains. In this context, a continuous time optimization problem is formulated to determine the optimal transmission and caching policies that minimize a generic cost function, such as energy, bandwidth, or throughput. The jointly optimal solution is obtained by demonstrating that caching files at a constant rate is optimal, which allows reformulation of the problem as a finite-dimensional convex program. The numerical results show that the proposed joint transmission and caching policy dramatically reduces the total cost, which is particularised to the total energy consumption at the Macro Base Station (MBS), as well as to the total economical cost for the service provider, when users demand economical incentives for delivering content to other users over the D2D links.


2016 - Zero-Delay Joint Source-Channel Coding in the Presence of Interference Known at the Encoder [Articolo su rivista]
Varasteh, M.; Gunduz, D.; Tuncel, E.
abstract

Zero-Delay transmission of a Gaussian source over an additive white Gaussian noise (AWGN) channel is considered in the presence of an independent additive Gaussian interference signal. The mean squared error (MSE) distortion is minimized under an average power constraint assuming that the interference signal is known at the transmitter. Optimality of simple linear transmission does not hold in this setting due to the presence of the known interference signal. While the optimal encoder-decoder pair remains an open problem, various non-linear transmission schemes are proposed in this paper. In particular, interference concentration (ICO) and one-dimensional lattice (1DL) strategies, using both uniform and non-uniform quantization of the interference signal, are studied. It is shown that, in contrast to typical scalar quantization of Gaussian sources, a non-uniform quantizer, whose quantization intervals become smaller as we go further from zero, improves the performance. Given that the optimal decoder is the minimum MSE (MMSE) estimator, a necessary condition for the optimality of the encoder is derived, and the numerically optimized encoder (NOE) satisfying this condition is obtained. Based on the numerical results, it is shown that 1DL with non-uniform quantization performs closer (compared with the other schemes) to the NOE while requiring significantly lower complexity.


2016 - Zero-delay joint source-channel coding with a 1-bit ADC front end and receiver side information [Relazione in Atti di Convegno]
Varasteh, M.; Rassouli, B.; Simeone, O.; Gunduz, D.
abstract

Zero-delay transmission of a Gaussian source over an additive white Gaussian noise (AWGN) channel with a 1-bit analog-to-digital converter (ADC) front end is investigated in the presence of correlated side information at the receiver. The design of the optimal encoder is considered for the mean squared error (MSE) distortion criterion under an average power constraint on the channel input. A necessary condition for the optimality of the encoder is derived. A numerically optimized encoder (NOE) is then obtained that aims that enforcing the necessary condition. It is observed that, due to the availability of receiver side information, the optimal encoder mapping is periodic, with its period depending on the correlation coefficient between the source and the side information. We then propose two parameterized encoder mappings, referred to as periodic linear transmission (PLT) and periodic BPSK transmission (PBT), which trade-off optimality for reduced complexity as compared to the NOE solution. We observe via numerical results that PBT performs close to the NOE in the high signal-to-noise ratio (SNR) regime, while PLT approaches the NOE performance in the low SNR regime.


2015 - Correlated Gaussian sources over Gaussian weak interference channels [Relazione in Atti di Convegno]
Aguerri, I. E.; Gunduz, D.
abstract

We consider the transmission of two correlated Gaussian sources over a Gaussian weak interference channel. Each transmitter has access to one component of a bivariate Gaussian source, and each of these components need to be reconstructed at the corresponding receiver, under the squared-error distortion measure. We are interested in characterizing the region of average distortion pairs achievable simultaneously at the two receivers. We derive an outer bound on the achievable region, and show that, under certain conditions, achievable distortion pair with uncoded transmission lies on this outer bound; therefore, it is optimal. In particular, optimality of uncoded transmission is shown to hold for all signal-to-noise ratio values below a certain threshold which depends on the correlation coefficient between the sources.


2015 - Delay constrained linear transmission of a mixture of Gaussian measurements over a fading channel [Relazione in Atti di Convegno]
Tan, O.; Gunduz, D.; Gomez-Vilardebo, J.
abstract

Delay constrained linear transmission (LT) of a mixture of Gaussian measurements over an additive white Gaussian noise (AWGN) fading channel is considered. At each time slot (TS), the control center (CC) asks for the measurement of a particular system parameter from the sensor, which is capable of measuring multiple independent system parameters. The average mean-square error (MSE) distortion is studied for Gaussian parameters and a Gaussian fading channel under an average power constraint. The optimal LT scheme is characterized under a strict delay constraint, and a graphical interpretation for the power allocation strategy is presented. Then, two achievable LT strategies are proposed for general delay constraints. It is shown that the performance improves as the delay constraint is relaxed, and when the delay constraint is completely removed, both strategies achieve the optimal performance under certain matching conditions.


2015 - Delay limited transmission of a uniform source over an AWGN channel [Relazione in Atti di Convegno]
Varasteh, Morteza; Gunduz, Deniz; Tuncel, Ertem
abstract

Delay limited transmission of a uniform source over an additive white Gaussian noise (AWGN) channel under an average power constraint is considered. Assuming that the channel can be used only once, mean squared error (MSE) distortion is studied for both the bandwidth matched, and the 2:1 bandwidth compression cases. In the bandwidth matched scenario, simply scaling the source sample, i.e., analog transmission, performs better than transmitting the scalar quantized source samples. For the bandwidth compression scenario, a hybrid digital analog transmission scheme that quantizes the first source sample and superimposes the quantized sample with the scaled version of the second sample is studied. It is shown that, in this scheme, as opposed to the bandwidth matched case, a finite number of quantization indices minimizes the achievable distortion. The performance of this hybrid scheme is then compared with a numerically optimized encoder using the steepest decent algorithm iteratively. It is observed that the performance of the hybrid scheme is reasonably close to the numerically optimized scheme, while having a significantly lower computational complexity. The theoretical Ziv-Zakai (ZZ) bound on the average distortion is also considered to better understand the gap between the optimal performance and the proposed scheme.


2015 - Distributed compression and transmission with energy harvesting sensors [Relazione in Atti di Convegno]
Gangula, R.; Gunduz, D.; Gesbert, D.
abstract

We determine the achievable distortion region when the correlated source samples are transmitted by two energy harvesting (EH) sensor nodes to the destination over orthogonal fading channels. A time slotted system is considered in which the energy and the source samples arrive at the beginning of each time slot (TS), and both the correlation between source samples at the two nodes and fading coefficients change over time but remain constant in each TS. Assuming non-causal knowledge of these time-varying source statistics, energy arrivals and the channel gains, i.e., under the offline optimization framework, we obtain the optimal transmission and coding schemes that achieve the points on the Pareto boundary of the total distortion region. An iterative directional 2D waterfilling algorithm is proposed to obtain two specific points on this boundary.


2015 - Gaussian joint source-channel coding for the strong interference channel [Relazione in Atti di Convegno]
Aguerri, I. E.; Gunduz, D.
abstract

Transmission of correlated Gaussian sources over a Gaussian interference channel is studied. Each terminal has one source available, which has to be reconstructed at the corresponding destination with the minimum average distortion. Focusing on the strong interference setting, we first derive necessary conditions on the achievable distortion pairs. Then, focusing on the symmetric scenario, we present achievable distortion pairs considering several transmission strategies. We compare the achievable distortion by the proposed schemes with the lower bound. In particular, we consider separate source and channel coding, uncoded transmission, a vector quantization (VQ) scheme which uses the quantization codewords as channel inputs, and finally a superposition of two quantization codewords. We show that the VQ scheme is optimal in the high SNR regime. We also show that the proposed superposition scheme performs very close to the lower bound in certain regimes.


2015 - Joint transmission and caching policy design for energy minimization in the wireless backhaul link [Relazione in Atti di Convegno]
Gregori, M.; Gomez-Vilardebo, J.; Matamoros, J.; Gunduz, D.
abstract

Caching the most popular contents at Small Base Stations (SBSs) is envisioned as a promising solution to reduce both the load and energy consumption of the backhaul link connecting the SBSs to the core network. This paper considers a set of users whose demands are served by an SBS connected through a wireless backhaul link to a Macro Base Station (MBS). The SBS is capable of caching content in its limited cache memory. The transmission policy at the MBS and the caching policy at the SBS are jointly optimized in order to minimize the energy consumption in the backhaul link. The numerical results show significant improvements with respect to prior works.


2015 - Multi-Access Communications With Energy Harvesting: A Multi-Armed Bandit Model and the Optimality of the Myopic Policy [Articolo su rivista]
Blasco, P.; Gunduz, D.
abstract

A multi-access wireless network with N transmitting nodes, each equipped with an energy harvesting (EH) device and a rechargeable battery of finite capacity, is studied. At each time slot (TS) a node is operative with a certain probability, which may depend on the availability of data, or the state of its channel. The energy arrival process at each node is modelled as an independent two-state Markov process, such that, at each TS, a node either harvests one unit of energy, or none. At each TS a subset of the nodes is scheduled by the access point (AP). The scheduling policy that maximises the total throughput is studied assuming that the AP does not know the states of either the EH processes or the batteries. The problem is identified as a restless multi-armed bandit (RMAB) problem, and an upper bound on the optimal scheduling policy is found. Under certain assumptions regarding the EH processes and the battery sizes, the optimality of the myopic policy (MP) is proven. For the general case, the performance of MP is compared numerically to the upper bound.


2015 - On the asymptotic distortion-energy tradeoff for zero-delay transmission of a Gaussian source over the AWGN channel [Relazione in Atti di Convegno]
Koken, E.; Tuncel, E.; Gunduz, D.
abstract

An achievable scheme for zero-delay transmission of an i.i.d. Gaussian source over an additive white Gaussian noise channel with no bandwidth limitation is introduced, and its energy-distortion performance is analyzed. By the nature of the problem, one must transmit each source sample separately but can use the channel infinitely many times. The proposed scheme builds on separation of source and channel coding, whereby the source is quantized into 'equiprobable' cells so that the output can be seen as a message suitable for channel coding. Moreover, as the number of quantization cells go to infinity, the channel capacity can be approached with arbitrarily small error. In the high energy-to-noise ratio regime, the minimum energy required to obtain a given distortion level in the proposed scheme can come as close as 3dB to the Shannon bound, which can only be achieved using infinite delay.


2015 - On the distortion-energy tradeoff for zero-delay transmission of a Gaussian source over the AWGN channel [Relazione in Atti di Convegno]
Koken, E.; Tuncel, E.; Gunduz, D.
abstract

An achievable scheme for zero-delay transmission of an i.i.d. Gaussian source over an additive white Gaussian channel with no bandwidth limitation is introduced, and its energy-distortion performance is analyzed. By the nature of the problem, one must transmit each source sample separately but can use the channel infinitely many times. We introduce an outage concept, and analyze the expected distortion conditioned on no outage. We show that the proposed scheme can approach to the asymptotical decay for large enough energy for arbitrary outage probability. The proposed scheme builds on separation of source and channel coding, whereby the source is quantized with a high-resolution optimal quantizer. In the high energy-to-noise ratio (ENR) regime, the minimum energy required to obtain a given distortion level in the proposed scheme can approach arbitrarily close the Shannon bound, which can only be achieved using infinite delay.


2015 - Optimal privacy-cost trade-off in demand-side management with storage [Relazione in Atti di Convegno]
Tan, O.; Gunduz, D.; Gomez-Vilardebo, J.
abstract

Demand-side energy storage management is studied from a joint privacy-energy cost optimization perspective. Assuming that the user's power demand profile as well as the electricity prices are known non-causally, the optimal energy management (EM) policy that jointly increases the privacy of the user and reduces his energy cost is characterized. The backward water-filling interpretation is provided for the optimal EM policy. While the energy cost is reduced by requesting more energy when the prices are lower, energy consumption privacy is achieved by a smoother output load. It is shown that both gains can be achieved by using a limited size storage unit. The optimal trade-off between the user's privacy and energy cost is characterized, and the impact of the size of the storage unit and the resolution of the smart meter readings on this trade-off is studied.


2015 - Optimization of Energy Harvesting MISO Communication System With Feedback [Articolo su rivista]
Gangula, R.; Gesbert, D.; Gunduz, D.
abstract

Optimization of a point-to-point (p2p) multiple-input single-output (MISO) communication system is considered when both the transmitter (TX) and the receiver (RX) have energy harvesting (EH) capabilities. The RX is interested in feeding back the channel state information (CSI) to the TX to help improve the transmission rate. The objective is to maximize the throughput by a deadline, subject to the EH constraints at the TX and the RX. The throughput metric considered is an upper bound on the ergodic rate of the MISO channel with beamforming and limited feedback. Feedback bit allocation and transmission policies that maximize the upper bound on the ergodic rate are obtained. Tools from majorization theory are used to simplify the formulated optimization problems. Optimal policies obtained for the modified problem outperform the naive scheme in which no intelligent management of energy is performed.


2015 - Smart meter privacy for multiple users in the presence of an alternative energy source [Articolo su rivista]
Gomez-Vilardebo, J.; Gunduz, D.
abstract

Smart meters (SMs) measure and report users' energy consumption to the utility provider (UP) in almost real-time, providing a much more detailed depiction of the consumer's energy consumption compared to their analog counterparts. This increased rate of information flow to the UP, together with its many potential benefits, raise important concerns regarding user privacy. This paper investigates, from an information theoretic perspective, the privacy that can be achieved in a multiuser SM system in the presence of an alternative energy source (AES). To measure privacy, we use the mutual information rate between the users' real energy consumption profile and SM readings that are available to the UP. The objective is to characterize the privacy-power function, defined as the minimal information leakage rate that can be obtained with an average power-limited AES. We characterize the privacy-power function in a single letter form when the users' energy demands are assumed to be independent and identically distributed over time. Moreover, for binary and exponentially distributed energy demands, we provide an explicit characterization of the privacy-power function. For any discrete energy demands, we demonstrate that the privacy-power function can always be efficiently evaluated numerically. Finally, for continuous energy demands, we derive an explicit lower bound on the privacy-power function, which is tight for exponentially distributed loads.


2015 - Source-channel coding under energy, delay, and buffer constraints [Articolo su rivista]
Orhan, O.; Gunduz, D.; Erkip, E.
abstract

Source and channel coding for an energy-limited wireless sensor node is investigated. The sensor node observes independent Gaussian source samples with variances changing over time slots. The channel is modeled as a flat fading channel, whose gain remains constant during each time slot, and changes from one time slot to the next. The compressed samples are stored in a finite data buffer, and need to be delivered to the destination in at most $d$ time slots. The objective is to minimize the average squared-error distortion between the source samples and their reconstructions. First, a battery operated system, in which the sensor node has a finite amount of energy at the beginning of transmission, is investigated. Then, the impact of energy harvesting, and the energy cost of processing and sampling are considered. The optimal compression and transmission policy is formulated as the solution of a convex optimization problem, and the properties of the optimal policies are identified. For the strict delay case, $d=1$, a two-dimensional $(2D) $ waterfilling interpretation is provided. Numerical results are presented to illustrate the structure of the optimal policy, and to analyze the effect of the delay constraints, data buffer size, energy harvesting, and processing and sampling costs.


2015 - Throughput and Delay Analysis in Video Streaming over Block-Fading Channels [Articolo su rivista]
Cocco, G.; Gunduz, D.; Ibars, C.
abstract

We study video streaming over a slow-fading wireless channel. In a streaming application, video packets are required to be decoded and displayed in the order they are transmitted as the transmission goes on. This results in per-packet delay constraints, and the resulting channel can be modeled as a physically degraded fading broadcast channel with as many virtual users as the number of packets. In this paper, we study two important quality of user experience (QoE) metrics, namely throughput and interdecoding delay. We introduce several transmission schemes, and compare their throughput and maximum interdecoding delay performances. We also introduce a genie-aided scheme, which provides theoretical bounds on the achievable performance. We observe that adapting the transmission rate at the packet level, i.e., periodically dropping a subset of the packets, leads to a good tradeoff between the throughput and the maximum interdecoding delay. We also show that an approach based on initial buffering leads to an asymptotically vanishing packet loss rate at the expense of a relatively large initial delay. For this scheme, we derive a condition on the buffering time that leads to throughput maximization.


2015 - Zero-delay joint source-channel coding in the presence of interference known at the encoder [Relazione in Atti di Convegno]
Varasteh, M.; Gunduz, D.; Tuncel, E.
abstract

Zero-delay transmission of a Gaussian source is considered over an additive white Gaussian noise (AWGN) channel in the presence of an additive Gaussian interference signal. The mean squared error (MSE) distortion is minimized under an average power constraint assuming that the interference signal is known causally at the transmitter. Optimality of simple uncoded transmission does not hold in this setting due to the presence of the known interference signal, and various non-linear transmission schemes are proposed. In particular, interference concentration (ICO) and one-dimensional lattice (1DL) strategies are studied. It is shown that non-uniform quantization of the interference signal for ICO improves the performance.


2014 - Delay constrained linear transmission of random state measurements [Relazione in Atti di Convegno]
Tan, O.; Gunduz, D.; Gomez-Vilardebo, J.
abstract

Linear transmission of state measurements is studied, where the control center (CC) sends random state measurement requests to multiple sensors. Each sensor is capable of measuring multiple system parameters, and the CC asks for a particular system parameter from each sensor at each time slot. Delay constrained linear transmission of these measurements over orthogonal fading channels is considered. The total meansquare error (MSE) distortion is studied for Gaussian states and channels under an average power constraint. For a particular symmetric scenario, a round-robin scheduling algorithm and optimal linear transmission (LT) scheme are presented. It is shown that, as opposed to the case of a single parameter measurement, the performance of the proposed LT strategy improves as the delay constraint is relaxed, and achieves the Shannon lower bound under certain matching conditions between the source and the channel statistics. © 2014 IEEE.


2014 - Designing intelligent energy harvesting communication systems [Articolo su rivista]
Gunduz, D.; Stamatiou, K.; Michelusi, N.; Zorzi, M.
abstract

From being a scientific curiosity only a few years ago, energy harvesting (EH) is well on its way to becoming a game-changing technology in the field of autonomous wireless networked systems. The promise of long-term, uninterrupted and self-sustainable operation in a diverse array of applications has captured the interest of academia and industry alike. Yet the road to the ultimate network of perpetual communicating devices is plagued with potholes: ambient energy is intermittent and scarce, energy storage capacity is limited, and devices are constrained in size and complexity. In dealing with these challenges, this article will cover recent developments in the design of intelligent energy management policies for EH wireless devices and discuss pressing research questions in this rapidly growing field. © 1979-2012 IEEE.


2014 - Energy harvesting broadband communication systems with processing energy cost [Articolo su rivista]
Orhan, O.; Gunduz, D.; Erkip, E.
abstract

Communication over a broadband fading channel powered by an energy harvesting transmitter is studied. Assuming non-causal knowledge of energy/data arrivals and channel gains, optimal transmission schemes are identified by taking into account the energy cost of the processing circuitry as well as the transmission energy. A constant processing cost for each active sub-channel is assumed. Three different system objectives are considered: 1) throughput maximization, in which the total amount of transmitted data by a deadline is maximized for a backlogged transmitter with a finite capacity battery; 2) energy maximization, in which the remaining energy in an infinite capacity battery by a deadline is maximized such that all the arriving data packets are delivered; and 3) transmission completion time minimization, in which the delivery time of all the arriving data packets is minimized assuming infinite size battery. For each objective, a convex optimization problem is formulated, the properties of the optimal transmission policies are identified, and an algorithm which computes an optimal transmission policy is proposed. Finally, based on the insights gained from the offline optimizations, low-complexity online algorithms performing close to the optimal dynamic programming solution for the throughput and energy maximization problems are developed under the assumption that the energy/data arrivals and channel states are known causally at the transmitter.


2014 - Energy harvesting communication system with a finite set of transmission rates [Relazione in Atti di Convegno]
Bodin, A.; Gunduz, D.
abstract

A point-to-point communication system in which the transmitter is equipped with an energy harvesting (EH) device and a rechargeable battery of limited size is considered. The harvested energy profile is assumed to be known in advance, that is, the problem is studied in the offline optimization framework. A practical communication system is considered, in which the possible transmission rates, and equivalently, power levels, belong to a finite set of discrete values. This problem is formulated as a convex optimization problem, which can be solved numerically. In order to provide further insights into the nature of the optimal transmission policy, an alternative solution is provided based on the solution of the continuous version of this problem, which itself has a "shortest path" interpretation. We propose an optimal algorithm, which permits us to easily build the solution of the discrete case from the continuous case, using an equivalence notion between different transmission policies, and several equivalence-preserving transformations.


2014 - Identification and lossy reconstruction in noisy databases [Articolo su rivista]
Tuncel, E.; Gunduz, D.
abstract

A high-dimensional database system is studied where the noisy versions of the underlying feature vectors are observed in both the enrollment and query phases. The noisy observations are compressed before being stored in the database, and the user wishes to both identify the correct entry corresponding to the noisy query vector and reconstruct the original feature vector within a desired distortion level. A fundamental capacity-storage-distortion tradeoff is identified for this system in the form of single-letter information theoretic expressions. The relation of this problem to the classical Wyner-Ziv rate-distortion problem is shown, where the noisy query vector acts as the correlated side information available only in the lossy reconstruction of the feature vector. © 1963-2012 IEEE.


2014 - Learning-based optimization of cache content in a small cell base station [Relazione in Atti di Convegno]
Blasco, P.; Gunduz, D.
abstract

Optimal cache content placement in a wireless small cell base station (sBS) with limited backhaul capacity is studied. The sBS has a large cache memory and provides content-level selective offloading by delivering high data rate contents to users in its coverage area. The goal of the sBS content controller (CC) is to store the most popular contents in the sBS cache memory such that the maximum amount of data can be fetched directly form the sBS, not relying on the limited backhaul resources during peak traffic periods. If the popularity profile is known in advance, the problem reduces to a knapsack problem. However, it is assumed in this work that, the popularity profile of the files is not known by the CC, and it can only observe the instantaneous demand for the cached content. Hence, the cache content placement is optimised based on the demand history. By refreshing the cache content at regular time intervals, the CC tries to learn the popularity profile, while exploiting the limited cache capacity in the best way possible. Three algorithms are studied for this cache content placement problem, leading to different exploitation-exploration trade-offs. We provide extensive numerical simulations in order to study the time-evolution of these algorithms, and the impact of the system parameters, such as the number of files, the number of users, the cache size, and the skewness of the popularity profile, on the performance. It is shown that the proposed algorithms quickly learn the popularity profile for a wide range of system parameters. © 2014 IEEE.


2014 - Multi-armed bandit optimization of cache content in wireless infostation networks [Relazione in Atti di Convegno]
Blasco, P.; Gunduz, D.
abstract

Optimal cache content placement is studied in a wireless infostation network (WIN), which models a limited coverage wireless network with a large cache memory. WIN provides content-level selective offloading by delivering high data rate contents stored in its cache memory to the users through a broadband connection. The goal of the WIN central controller (CC) is to store the most popular content in the cache memory of the WIN such that the maximum amount of data can be fetched directly from the cache rather than being downloaded from the core network. If the popularity profile of the available set of contents is known in advance, the optimization of the cache content reduces to a knapsack problem. However, it is assumed in this work that the popularity profile of the files is not known, and only the instantaneous demands for those contents stored in the cache can be observed. Hence, the cache content placement is optimised based on the demand history, and on the cost associated to placing each content in the cache. By refreshing the cache content at regular time intervals, the CC tries to learn the popularity profile, while at the same time exploiting the limited cache capacity in the best way possible. This problem is formulated as a multi-armed bandit problem with switching cost, and an algorithm to solve it is presented. The performance of the algorithm is measured in terms of regret, which is proven to be logarithmic and sub-linear uniformly over time for a specific and a general case, respectively. © 2014 IEEE.


2014 - On joint source-channel coding for correlated sources over multiple-access relay channels [Articolo su rivista]
Murin, Y.; Dabora, R.; Gunduz, D.
abstract

We study the transmission of correlated sources over discrete memoryless (DM) multiple-access-relay channels (MARCs), in which both the relay and the destination have access to side information arbitrarily correlated with the sources. As the optimal transmission scheme is an open problem, in this paper, we propose a new joint source-channel coding scheme based on a novel combination of the correlation preserving mapping (CPM) technique with Slepian-Wolf (SW) source coding, and obtain the corresponding sufficient conditions. The proposed coding scheme is based on the decode-and-forward strategy, and utilizes CPM for encoding information simultaneously to the relay and the destination, whereas the cooperation information from the relay is encoded via SW source coding. It is shown that there are cases in which the new scheme strictly outperforms the schemes available in the literature. This is the first instance of a source-channel code that uses CPM for encoding information to two different nodes (relay and destination). In addition to sufficient conditions, we present three different sets of single-letter necessary conditions for reliable transmission of correlated sources over DM MARCs. The newly derived conditions are shown to be at least as tight as the previously known necessary conditions.


2014 - Uncoded transmission of correlated Gaussian sources over broadcast channels with feedback [Relazione in Atti di Convegno]
Murin, Y.; Kaspi, Y.; Dabora, R.; Gunduz, D.
abstract

Motivated by the practical requirement for delay and complexity constrained broadcasting, we study uncoded transmission of a pair of correlated Gaussian sources over a two-user Gaussian broadcast channel with unit-delay noiseless feedback links (GBCF). Differently from previous works, in the present work we focus on the finite horizon regime. We present two joint source-channel coding schemes, one is based on the Ozarow-Leung (OL) coding scheme for the GBCF and the other is based on the linear quadratic Gaussian (LQG) code by Ardestanizadeh et al. Our LQG-oriented code uses an improved decoder which outperforms the original decoder of Ardestanizadeh et al. in the finite horizon regime. We further derive lower and upper bounds on the minimal number of channel uses needed to achieve a specified pair of distortion levels for each scheme, and using these bounds, we explicitly characterize a range of transmit powers in which the OL code outperforms the LQG-oriented code.


2014 - Zero-delay joint source-channel coding [Relazione in Atti di Convegno]
Aguerri, I. E.; Varasteh, M.; Gunduz, D.
abstract

In zero-delay joint source-channel coding each source sample is mapped to a channel input, and the samples are directly estimated at the receiver based on the corresponding channel output. Despite its simplicity, uncoded transmission achieves the optimal end-to-end distortion performance in some communication scenarios, significantly simplifying the encoding and decoding operations, and reducing the coding delay. Three different communication scenarios are considered here, for which uncoded transmission is shown to achieve either optimal or near-optimal performance. First, the problem of transmitting a Gaussian source over a block-fading channel with block-fading side information is considered. In this problem, uncoded linear transmission is shown to achieve the optimal performance for certain side information distributions, while separate source and channel coding fails to achieve the optimal performance. Then, uncoded transmission is shown to be optimal for transmitting correlated multivariate Gaussian sources over a multiple-input multiple-output (MIMO) channel in the low signal to noise ratio (SNR) regime. Finally, motivated by practical systems a peak-power constraint (PPC) is imposed on the transmitter's channel input. Since linear transmission is not possible in this case, nonlinear transmission schemes are proposed and shown to perform very close to the lower bound. © 2014 IEEE.


2013 - A learning theoretic approach to energy harvesting communication system optimization [Articolo su rivista]
Blasco, P.; Gunduz, D.; Dohler, M.
abstract

A point-to-point wireless communication system in which the transmitter is equipped with an energy harvesting device and a rechargeable battery, is studied. Both the energy and the data arrivals at the transmitter are modeled as Markov processes. Delay-limited communication is considered assuming that the underlying channel is block fading with memory, and the instantaneous channel state information is available at both the transmitter and the receiver. The expected total transmitted data during the transmitter's activation time is maximized under three different sets of assumptions regarding the information available at the transmitter about the underlying stochastic processes. A learning theoretic approach is introduced, which does not assume any a priori information on the Markov processes governing the communication system. In addition, online and offline optimization problems are studied for the same setting. Full statistical knowledge and causal information on the realizations of the underlying stochastic processes are assumed in the online optimization problem, while the offline optimization problem assumes non-causal knowledge of the realizations in advance. Comparing the optimal solutions in all three frameworks, the performance loss due to the lack of the transmitter's information regarding the behaviors of the underlying Markov processes is quantified. © 2002-2012 IEEE.


2013 - Energy harvesting communication networks: Optimization and demonstration (The E-CROPS project) [Relazione in Atti di Convegno]
Gelenbe, E.; Gesbert, D.; Gunduz, D.; Kulah, H.; Uysal-Biyikoglu, E.
abstract

We describe the new European project E-CROPS which was ranked first in the 2012 CHIST-ERA competition. This project has begun its work in February 2013 to develop a system-wide approach to using energy harvesting and smart energy management technologies in communication and mobile devices. The project will examine energy-dependent fundamental limits of communications, together with the timely harvesting, storage and delivery of energy to the computing and communication units of these devices, to achieve an optimal balance between the quality of service, performance, and efficient usage of energy. E-CROPS will combine theoretical modelling and performance analysis with experimental demonstrations bringing together four collaborating teams from France (EURECOM), Spain (CTTC), Turkey (METU) and the UK (Imperial College London). © 2013 IEEE.


2013 - Increasing smart meter privacy through energy harvesting and storage devices [Articolo su rivista]
Tan, O.; Gunduz, D.; Poor, H. V.
abstract

Smart meters are key elements for the operation of smart grids. By providing near realtime information on the energy consumption of individual users, smart meters increase the efficiency in generation, distribution and storage of energy in a smart grid. The ability of the utility provider to track users' energy consumption inevitably leads to important threats to privacy. In this paper, privacy in a smart metering system is studied from an information theoretic perspective in the presence of energy harvesting and storage units. It is shown that energy harvesting provides increased privacy by diversifying the energy source, while a storage device can be used to increase both the energy efficiency and the privacy of the user. For given input load and energy harvesting rates, it is shown that there exists a trade-off between the information leakage rate, which is used to measure the privacy of the user, and the wasted energy rate, which is a measure of the energy-efficiency. The impact of the energy harvesting rate and the size of the storage device on this trade-off is also studied. © 1983-2012 IEEE.


2013 - Information theoretic privacy for smart meters [Relazione in Atti di Convegno]
Gunduz, D.; Gomez-Vilardebo, J.; Tan, O.; Poor, V.
abstract

Smart meters (SMs) measure and report energy consumption of individual users to the utility provider at short intervals on the order of minutes. While SM data is used to increase the efficiency in electricity distribution, it also conveys sensitive private data on the energy consumption behaviour of individual customers. In this work, privacy in a smart metering system is studied from an information theoretic perspective in the presence of alternative energy sources and storage units. An alternative energy source provides increased privacy by diversifying the energy source, and the storage device filters the real energy consumption to reduce the leaked data. Connections between this problem and rate-distortion theory is established, and both theoretical and numerical results are presented. © 2013 IEEE.


2013 - On necessary conditions for multiple-access-relay channels with correlated sources [Relazione in Atti di Convegno]
Murin, Y.; Dabora, R.; Gunduz, D.
abstract

The characterization of the optimal joint source-channel coding scheme for transmission of correlated sources over multiple-access-relay channels (MARCs) is an open problem. Here, this problem is studied in the presence of arbitrarily correlated side information at both the relay and the destination. Since each transmitter observes only one of the sources, the admissible joint distributions of the sources and channel inputs must satisfy a Markov relationship which constrains their statistical dependence. This observation is used together with the new data processing inequality derived by [Kang and Ulukus, 2011] to obtain two new sets of single-letter necessary conditions. These new conditions are shown to be at least as tight as the previously known ones, and strictly tighter than the cut-set bound. © 2013 IEEE.


2013 - Optimal packet scheduling for an energy harvesting transmitter with processing cost [Relazione in Atti di Convegno]
Orhan, O.; Gunduz, D.; Erkip, E.
abstract

Energy harvesting (EH) technology enables wireless nodes to operate in a self-powered fashion; however, the stochastic nature of the harvesting process and the limited amount of harvested energy require efficient management of the available resources. In this paper, an EH transmitter communicating over a fading channel is studied considering jointly the energy costs of transmission and processing. In particular, under the assumption of known energy and data arrival profiles and fading states, optimal transmission policies are studied, so that, the remaining energy in the battery of the transmitter is maximized by a given deadline while all the arriving data packets are delivered to the receiver. A 'directional glue pouring' interpretation is provided for the algorithm that computes the optimal offline transmission policy. The relation of this problem with the transmission completion time minimization problem is also discussed. Finally, a heuristic algorithm for online optimization, which performs close to the optimal offline transmission policy, is proposed. © 2013 IEEE.


2013 - Optimum power level for communications with interference [Relazione in Atti di Convegno]
Gelenbe, E.; Gunduz, D.
abstract

As part of the CHIST-ERA E-CROPS Project we analyze the appropriate choice of transmission power in a collection of identical electronic systems that process and transmit data over a common channel, in the presence of noise and interference. Our analysis shows that, depending on whether the receiver or the sender is used to mitigate for errors, the power level will influence the energy consumption per bit via both the power and the effective transmission time, since transmission power is a source of interference and hence of errors. The analyis is carried out for receiver controlled retransmission requests when errors are sensed, and alsofor a scheme where the sender uses carrier sensing to infer the likelihood of a transmission error. The issue is also discussed for wired digital system where crosstalk is the source of interference. © 2013 IEEE.


2013 - Privacy of smart meter systems with an alternative energy source [Relazione in Atti di Convegno]
Gomez-Vilardebo, J.; Gunduz, D.
abstract

Smart meter (SM) measurements provide near realtime information on the electricity consumption of a user to the utility provider (UP). This data can be used to extract private information on the energy consumption patterns of the user. Assuming that the user has access to an alternative energy source (AES) in addition to the power grid, SM privacy problem is studied from an information theoretic perspective. The energy requirement of the user (input load) at each time instant can be satisfied either from the power grid (output load) or from the AES. It is assumed that the output load can be perfectly tracked by the UP, and the privacy is measured through the information leakage rate. For given average and peak power constraints on the AES, privacy-power function is defined, and its equivalence to the rate-distortion function with a difference distortion measure is shown. Focusing on continuous input loads, the privacy-power function is characterized when there is only peak power limitation on the AES, while the Shannon lower bound is provided for the general case. The bound is shown to be achievable for the exponential input distribution. © 2013 IEEE.


2013 - Reliable joint source-channel cooperative transmission over relay networks [Articolo su rivista]
Gunduz, D.; Erkip, E.; Goldsmith, A.; Poor, H. V.
abstract

Reliable transmission of a discretememoryless source to multiple destinations over a relay network is considered. Motivated by sensor network applications, it is assumed that the relays and the destinations all have access to side information correlated with the underlying source signal. Joint source-channel cooperative transmission is studied in which the terminals in the network help the transmission of the source signal to the destinations by using their overheard signals, as in the classical channel cooperation scenario, as well as the available correlated side information. Decode-and-forward-based cooperative transmission is studied in a network of multiple relay terminals and two different achievability schemes are proposed: 1) a regular encoding and slidingwindow decoding scheme without explicit source binning at the encoder; and 2) a semiregular encoding and backward decoding scheme with binning based on the side information statistics. It is shown that both of these schemes lead to the same source-channel code rate, which is shown to be the source-channel capacity in the case of 1) a physically degraded relay networkwith a single destination in which the side information signals are degraded in the same order as the channel; and 2) a relay network with multiple destinations, in which all the terminals want to reconstruct the source reliably, while at most one of them can act as a relay.© 2012 IEEE.


2013 - Source-channel coding theorems for the multiple-access relay channel [Articolo su rivista]
Murin, Y.; Dabora, R.; Gunduz, D.
abstract

We study reliable transmission of arbitrarily correlated sources over multiple-access relay channels (MARCs) and multiple-access broadcast relay channels (MABRCs). In MARCs only the destination is interested in reconstructing the sources, while in MABRCs, both the relay and the destination want to reconstruct them. In addition to arbitrary correlation among the source signals at the users, both the relay and the destination have side information correlated with the source signals. Our objective is to determine whether a given pair of sources can be losslessly transmitted to the destination for a given number of channel symbols per source sample, defined as the source-channel rate. Sufficient conditions for reliable communication based on operational separation, as well as necessary conditions on the achievable source-channel rates are characterized. Since operational separation is generally not optimal for MARCs and MABRCs, sufficient conditions for reliable communication using joint source-channel coding schemes based on a combination of the correlation preserving mapping technique with Slepian-Wolf source coding are also derived. For correlated sources transmitted over fading Gaussian MARCs and MABRCs, we present conditions under which separation (i.e., separate and stand-alone source and channel codes) is optimal. This is the first time optimality of separation is proved for MARCs and MABRCs. © 1963-2012 IEEE.


2013 - Streaming transmission over block fading channels with delay constraint [Articolo su rivista]
Cocco, G.; Gunduz, D.; Ibars, C.
abstract

Streaming transmission over a block fading channel is studied assuming that the transmitter receives a new message at each channel block at a constant rate, which is fixed by an underlying application. A common deadline is assumed for all the messages, at which point the receiver tries to decode as many messages as possible. Various achievable schemes are proposed and compared with an informed transmitter upper bound in terms of average throughput. It is shown that the adaptive joint encoding (aJE) scheme is asymptotically optimal; that is, it achieves the ergodic capacity as the transmission deadline goes to infinity; and it closely follows the upper bound in the case of a finite transmission deadline. On the other hand, in the presence of multiple receivers with different signal-to-noise ratios (SNR), memoryless transmission (MT), generalized time-sharing (gTS) and superposition transmission (ST) schemes are shown to be more robust than the joint encoding (JE) scheme as they have gradual performance degradation with the decreasing SNR. © 2013 IEEE.


2013 - Systematic lossy source transmission over Gaussian time-varying channels [Relazione in Atti di Convegno]
Aguerri, I. E.; Gunduz, D.
abstract

Systematic lossy transmission of a Gaussian source over a time-varying Gaussian channel is considered. A noisy version of the source is transmitted in an uncoded fashion to the destination through a time-varying Gaussian 'base channel', constituting the systematic part of the transmission. A second time-varying Gaussian channel, called the 'enhancement channel', orthogonal to the first one, is available for coded transmission of the source sequence. A block fading model for both channels is considered, and the average end-to-end distortion is studied assuming perfect channel state information only at the receiver. It is shown that if the enhancement channel is static and the base channel gain has a discrete or continuous-quasiconcave distribution, then the separation theorem applies. However, when both channels are block fading, separation theorem does not hold anymore. A lower bound is obtained by providing the enhancement channel state to the encoder, and it is shown that uncoded transmission is exactly optimal for certain base channel fading distributions, while the enhancement channel fading has arbitrary distribution. A joint decoding scheme is also presented and is shown to outperform uncoded transmission and separate source and channel coding for other base channel distributions. © 2013 IEEE.


2013 - The multiway relay channel [Articolo su rivista]
Gunduz, D.; Yener, A.; Goldsmith, A.; Poor, V.
abstract

The multiuser communication channel, in which multiple users exchange information with the help of a relay terminal, termed the multiway relay channel (mRC), is introduced. In this model, multiple interfering clusters of users communicate simultaneously, such that the users within the same cluster wish to exchange messages among themselves, i.e., each user multicasts its message to all the other users in its own cluster. It is assumed that the users cannot receive each other's signals directly. Hence, the relay terminal in this model is the enabler of communication. In particular, restricted encoders are considered, such that the encoding function of each user depends only on its own message and the received signal is used only for decoding the messages of the other users in the cluster. Achievable rate regions and an outer bound are characterized for the Gaussian mRC, and their comparison is presented in terms of the exchange rate, the symmetric rate point in the capacity region in a symmetric Gaussian mRC scenario. It is shown that the compress-and-forward (CF) protocol achieves exchange rates within a constant bit offset of the optimal exchange rate, independent of the power constraints of the terminals in the network. A finite bit gap between the exchange rates achieved by the CF and the amplify-and-forward protocols is also shown. The two special cases of the mRC, the full data exchange model, in which every user wants to receive messages of all other users, and the pairwise data exchange model which consists of multiple two-way relay channels, are investigated in detail. In particular for the pairwise data exchange model, in addition to the proposed random coding-based achievable schemes, a nested lattice coding-based scheme is also presented and is shown to achieve exchange rates within a constant bit gap of the exchange capacity. © 2012 IEEE.


2013 - Throughput and delay analysis in video streaming over block-fading channels [Relazione in Atti di Convegno]
Cocco, G.; Gunduz, D.; Ibars, C.
abstract

In a streaming application video packets are required to be decoded and displayed in the order they are transmitted as the transmission continues. This results in perpacket delay constraints, and in the wireless setting the resulting channel can be modeled as a physically degraded fading broadcast channel with as many virtual users as the number of packets. Two important quality of user experience (QoE) metrics, throughput and inter-decoding delay, are considered jointly, and lower and upper bounds on both metrics are presented. © 2013 IEEE.


2012 - A General Framework for the Optimization of Energy Harvesting Communication Systems with Battery Imperfections [Articolo su rivista]
Devillers, B.; Gunduz, D.
abstract

Energy harvesting has emerged as a powerful technology for complementing current battery-powered communication systems in order to extend their lifetime. In this paper a general framework is introduced for the optimization of communication systems in which the transmitter is able to harvest energy from its environment. Assuming that the energy arrival process is known non-causally at the transmitter, the structure of the optimal transmission scheme, which maximizes the amount of transmitted data by a given deadline, is identified. Our framework includes models with continuous energy arrival as well as battery constraints. A battery that suffers from energy leakage is studied further, and the optimal transmission scheme is characterized for a constant leakage rate. © 2012 KICS


2012 - Capacity of a class of relay channels with state [Relazione in Atti di Convegno]
Aguerri, I. E.; Gunduz, D.
abstract

The class of orthogonal relay channels with state in which the source and the relay are connected through a channel that depends on a state sequence is considered. It is assumed that the state sequence is fully known at the destination while it is not known at the source or the relay. The source and the relay are connected to the destination through orthogonal channels. The capacity of this class of relay channels is characterized and it is shown to be achieved by the partial decode-compress-and-forward (pDCF) scheme. To the best of our knowledge, this is the first single relay channel model for which the capacity is achieved by pDCF, while partial decode-and-forward (pDF) and compress-and-forward (CF) schemes are suboptimal in general. © 2012 IEEE.


2012 - Energy-distortion tradeoffs in Gaussian joint source-channel coding problems [Articolo su rivista]
Jain, A.; Gunduz, D.; Kulkarni, S.; Poor, H. V.; Verdu, S.
abstract

The information-theoretic notion of energy efficiency is studied in the context of various joint source-channel coding problems. The minimum transmission energy E(D) required to communicate a source over a noisy channel so that it can be reconstructed within a target distortion D is analyzed. Unlike the traditional joint source-channel coding formalisms, no restrictions are imposed on the number of channel uses per source sample. For single-source memoryless point-to-point channels, E(D)is shown to be equal to the product of the minimum energy per bit {E bmin of the channel and the rate-distortion function R(D) of the source, regardless of whether channel output feedback is available at the transmitter. The primary focus is on Gaussian sources and channels affected by additive white Gaussian noise under quadratic distortion criteria, with or without perfect channel output feedback. In particular, for two correlated Gaussian sources communicated over a Gaussian multiple-access channel, inner and outer bounds on the energy-distortion region are obtained, which coincide in special cases. For symmetric channels, the difference between the upper and lower bounds on energy is shown to be at most a constant even when the lower bound goes to infinity as D to 0. It is also shown that simple uncoded transmission schemes perform better than the separation-based schemes in many different regimes, both with and without feedback. © 2011 IEEE.


2012 - Joint source-channel coding for the multiple-access relay channel [Relazione in Atti di Convegno]
Murin, Y.; Dabora, R.; Gunduz, D.
abstract

Reliable transmission of arbitrarily correlated sources over multiple-access relay channels (MARCs) and multiple-access broadcast relay channels (MABRCs) is considered. In MARCs, only the destination is interested in a reconstruction of the sources, while in MABRCs, both the relay and the destination want to reconstruct the sources. We allow an arbitrary correlation among the sources at the transmitters, and let both the relay and the destination have side information that are correlated with the sources. Two joint source-channel coding schemes are presented and the corresponding sets of sufficient conditions for reliable communication are derived. The proposed schemes use a combination of the correlation preserving mapping (CPM) technique with Slepian-Wolf (SW) source coding: the first scheme uses CPM for encoding information to the relay and SW source coding for encoding information to the destination; while the second scheme uses SW source coding for encoding information to the relay and CPM for encoding information to the destination. © 2012 IEEE.


2012 - Throughput maximization for an energy harvesting communication system with processing cost [Relazione in Atti di Convegno]
Orhan, O.; Gunduz, D.; Erkip, E.
abstract

In wireless networks, energy consumed for communication includes both the transmission and the processing energy. In this paper, point-to-point communication over a fading channel with an energy harvesting transmitter is studied considering jointly the energy costs of transmission and processing. Under the assumption of known energy arrival and fading profiles, optimal transmission policy for throughput maximization is investigated. Assuming that the transmitter has sufficient amount of data in its buffer at the beginning of the transmission period, the average throughput by a given deadline is maximized. Furthermore, a 'directional glue pouring algorithm' that computes the optimal transmission policy is described. © 2012 IEEE.


2011 - Capacity results for a class of deterministic Z-interference channels with unidirectional receiver conferencing [Relazione in Atti di Convegno]
Liu, N.; Gunduz, D.; Kang, W.
abstract

We study the Z-interference channel in which there is an additional orthogonal link from the interference-free receiver to the interfered receiver. We call this channel model the Z-interference channel with unidirectional receiver conferencing. We find the capacity region when the Z-interference channel belongs to the class of deterministic Z-interference channels studied by El Gamal & Costa in 1982. Our results show that in the presence of unidirectional receiver conferencing, it is still optimal for the interfering transmitter to use superposition encoding to control the amount of interference it causes. For the interference-free receiver, it is optimal to forward part of the decoded message over the orthogonal cooperation link. We further note that the same scheme is also optimal for another class of Z-interference channels studied by Liu & Goldsmith in 2009. © 2011 IEEE.


2011 - Collision resolution in slotted ALOHA with multi-user physical-layer network coding [Relazione in Atti di Convegno]
Cocco, G.; Ibars, C.; Gunduz, D.; del Rio Herrero, O.
abstract

Two new schemes are proposed for collision resolution in slotted ALOHA networks based on multi-user physicallayer network coding (MU PHY NC). In the proposed random access schemes, a collision of a generic number of packets can be recovered decoding the XOR of the original messages, such that the signal resulting from the collision is exploited rather than being discarded. Two different schemes that differ in terms of the amount of control information that needs to be transmitted from the access point, are studied. © 2011 IEEE.


2011 - Distortion exponent in fading MIMO channels with time-varying side information [Relazione in Atti di Convegno]
Aguerri, I. E.; Gunduz, D.
abstract

The joint source-channel coding problem of sending a Gaussian source over a multiple input-multiple output (MIMO) fading channel with time-varying correlated side information at the decoder is studied. A block fading model for both the channel and the side information qualities is considered, and perfect (channel and side information) state information at the receiver is assumed, while the transmitter has only a statistical knowledge. In particular, the high SNR performance is studied by deriving the distortion exponent of various transmission schemes. An upper bound on the distortion exponent is derived by providing the channel state to the encoder while the side information state remains unknown. Separate source and channel coding is considered as well as joint decoding at the receiver. The joint decoding scheme is extended to multiple digital layers. Finally, a hybrid digital-analog (HDA) scheme is analyzed. While the optimal distortion exponent is completely characterized for MISO/SIMO channels, for general MIMO channels, the optimal distortion exponent is characterized in the small bandwidth ratio regime. © 2011 IEEE.


2011 - Expected distortion with fading channel and side information quality [Relazione in Atti di Convegno]
Aguerri, I. E.; Gunduz, D.
abstract

We consider the joint source-channel coding problem of sending a Gaussian source over a single input-single output (SISO) fading channel when the decoder has additional correlated side information whose quality is also time-varying. We assume a block fading model for both the channel and side information qualities, and assume perfect state information at the receiver, while the transmitter has only a statistical knowledge. We are interested in the expected squared-error distortion for this system. We study separate source-channel coding,uncoded transmission and a joint source-channel transmission scheme based on joint decoding at the receiver. We then extend joint decoding scheme technique to hybrid digital-analog and multi-layer schemes. We provide numerical results in the finite SNR regime, and derive closed form expressions for the distortion exponent in the high SNR regime. © 2011 IEEE.


2011 - Real-time broadcasting over block-fading channels [Relazione in Atti di Convegno]
Cocco, G.; Gunduz, D.; Ibars, C.
abstract

Broadcast transmission from a base station (BS) to a group of users is studied. It is assumed that the BS receives data at a constant rate and tries to broadcast these messages to the whole set of users within a certain deadline. The channels are assumed to be block fading and independent over blocks and users. Our performance measure is the total rate of received information at the users within the transmission deadline. Three different encoding schemes are proposed, and they are compared with an informed transmitter upper bound in terms of the average total reception rate for a set of users with varying channel qualities. It is shown that no single transmission strategy dominates for all channel settings, and the best broadcasting technique depends on the distribution of the average channel conditions over the users. © 2011 IEEE.


2011 - Throughput analysis in asymmetric two-way relay channel with random access [Relazione in Atti di Convegno]
Cocco, G.; Gunduz, D.; Ibars, C.
abstract

We consider the two-way relay channel with random access for the cases of symmetric and asymmetric channel statistics in the low SNR regime. We propose three different schemes implementing different physical layer techniques for collision recovery and channel adaptation and obtain analytical throughput expressions. We compare the proposed schemes with several benchmarks in order to study their bandwidth gains in practical scenarios. © 2011 IEEE.


2011 - Two-hop communication with energy harvesting [Relazione in Atti di Convegno]
Gunduz, D.; Devillers, B.
abstract

Communication nodes with the ability to harvest energy from the environment have the potential to operate beyond the timeframe limited by the finite capacity of their batteries; and accordingly, to extend the overall network lifetime. However, the optimization of the communication system in the presence of energy harvesting devices requires a new paradigm in terms of power allocation since the energy becomes available over time. In this paper, we consider the problem of two-hop relaying in the presence of energy harvesting nodes. We identify the optimal offline transmission scheme for energy harvesting source and relay when the relay operates in the full-duplex mode. In the case of a half-duplex relay, we provide the optimal transmission scheme when the source has a single energy packet. © 2011 IEEE.


2010 - Cooperative relaying in sensor networks [Relazione in Atti di Convegno]
Gunduz, D.; Erkip, E.; Goldsmith, A.; Poor, H. V.
abstract

Reliable transmission of a discrete memoryless source over a multiple-relay network is considered. Motivated by sensor network applications, it is assumed that the relays and the destination all have access to side information correlated with the underlying source signal. Joint source-channel cooperative transmission is studied in which the relays help the transmission of the source signal to the destination by using both their overheard signals, as in the classical channel cooperation scenario, and the available correlated side information. Decode-and-forward (DF) based cooperative transmission is considered in a network of multiple relay terminals and two different achievability schemes are proposed: i) a regular encoding and sliding-window decoding scheme with no binning at the encoder, and ii) a semi-regular encoding and backward decoding scheme with explicit binning based on the side information statistics. It is shown that both of these schemes lead to the same sufficiency conditions, which are shown to be also necessary in the case of a physically degraded relay network in which the side information signals are also degraded in the same order.


2010 - Energy efficient lossy transmission over sensor networks with feedback [Relazione in Atti di Convegno]
Jain, A.; Gunduz, D.; Kulkarni, S.; Poor, H. V.; Verdu, S.
abstract

The energy-distortion function (E(D)) for a network is defined as the minimum total energy required to achieve a target distortion D at the receiver without putting any restrictions on the number of channel uses per source sample. E(D) is studied for a sensor network in which multiple sensors transmit their noisy observations of a Gaussian source to the destination over a Gaussian multiple access channel with perfect channel output feedback. While the optimality of separate source and channel coding is proved for the case of a single sensor, this optimality is shown to fail when there are multiple sensors in the network. A network with two sensors is studied in detail. First a lower bound on E(D) is given. Then, two achievability schemes are proposed: a separation based digital scheme and a Schalkwijk-Kailath (SK) type uncoded scheme. The gap between the lower bound and the upper bound based on separation is shown to be a constant even as the total energy requirement goes to infinity in the low distortion regime. On the other hand, as the distortion requirement is relaxed, the SK based scheme is shown to outperform separation in certain cases, proving that the optimality of source-channel separation does not hold in the multi-sensor setting. ©2010 IEEE.


2010 - Energy-distortion tradeoff with multiple sources and feedback [Relazione in Atti di Convegno]
Jain, A.; Gunduz, D.; Kulkarni, S.; Poor, H. V.; Verdu, S.
abstract

The energy-distortion tradeoff for lossy transmission of sources over multi-user networks is studied. The energy-distortion function E(D) is defined as the minimum energy required to transmit a source to the receiver within the target distortion D, when there is no restriction on the number of channel uses per source sample. For point-to-point channels, E(D) is shown to be equal to the product of the minimum energy per bit Ebmin and the rate-distortion function R(D), indicating the optimality of source-channel separation in this setting. It is shown that the optimal E(D) can also be achieved by the Schalkwijk-Kailath (SK) scheme, as well as separate coding, in the presence of perfect channel output feedback. Then, it is shown that the optimality of separation in terms of E(D) does not extend to multi-user networks. The scenario with two encoders observing correlated Gaussian sources in which the encoders communicate to the receiver over a Gaussian multiple-access channel (MAC) with perfect channel output feedback is studied. First a lower bound on E(D) is provided and compared against two upper bounds achievable by separation and an uncoded SK type scheme, respectively. Even though neither of these achievable schemes meets the lower bound in general, it is shown that their energy requirements lie within a constant gap of E(D) in the low distortion regime, for which the energy requirement grows unbounded. It is shown that the SK based scheme outperforms the separation based scheme in certain scenarios, which establishes the sub-optimality of separation in this multi-user setting.


2010 - Energy-distortion tradeoffs in multiple-access channels with feedback [Relazione in Atti di Convegno]
Jain, A.; Gunduz, D.; Kulkarni, S.; Poor, H. V.; Verdu, S.
abstract

The energy-distortion function E(D) for the joint source-channel coding problem in networks is defined and studied. The energy-distortion function E(D) is defined as the minimum energy required to transmit a source to a receiver within the target distortion D, when there is no restriction on the number of channel uses per source sample. For point-to-point channels, E(D) is shown to be equal to the product of the minimum energy per bit Ebmin and the rate-distortion function R(D), establishing the optimality of source-channel separation in this setting. Then, it is shown that the optimality of separation does not extend to multi-user networks. A scenario with two encoders observing correlated Gaussian sources in which the encoders communicate to the receiver over a Gaussian multiple-access channel (MAC) with perfect channel output feedback is studied. First a lower bound on E(D) is provided and compared against an upper bound achievable by separation. Even though the separation based scheme does not achieve the lower bound in general, its energy requirement is shown to be within a constant gap of E(D) in the low distortion regime, for which the energy requirement grows unbounded. Another upper bound using uncoded transmission based on the well-known Schalkwijk-Kailath (SK) scheme is also considered. Through simulation, it is shown that this scheme outperforms the separation based scheme in various scenarios, thus establishing the sub-optimality of separation in this model of multiple users with correlated sources.


2010 - Gaussian two-way relay channel with arbitrary inputs [Relazione in Atti di Convegno]
Gunduz, D.; Payaro, M.
abstract

A two-way relay channel with independent parallel Gaussian channels between the relay and the two terminals is considered. Focusing on the decode-and-forward protocol, the second phase of the communication, in which the relay broadcasts the two messages to their respective receivers, is studied. Precisely, the problem of computing the power allocation among the parallel channels that maximizes the weighted sum rate assuming arbitrarily distributed channel inputs (such as m-QAM) is stated and shown to be convex. A numerical algorithm is provided to solve the problem for the general case and, for the particular cases of high and low power regimes, expressions for the optimal power allocation are derived in closed form. ©2010 IEEE.


2010 - Hybrid digital-analog transmission for the gaussian one-helper problem [Relazione in Atti di Convegno]
Aguerri, I. E.; Gunduz, D.
abstract

The one-helper joint source-channel coding problem, in which a main source is to be reconstructed with minimum distortion with the help of a correlated helper source, is studied. Focusing on the case of Gaussian sources and a Gaussian multiple access channel (MAC), a generalized hybrid digital-analog scheme is proposed, in which each user allocates its available power among the analog and digital signals and transmits a superposition of the two. It is shown that this generalized hybrid scheme reduces to pure analog or pure digital transmission depending on the system parameters. Finally, the optimal hybrid transmission strategy is identified analytically in certain special scenarios modeling legacy systems. ©2010 IEEE.


2010 - Identification and lossy reconstruction in noisy databases [Relazione in Atti di Convegno]
Tuncel, E.; Gunduz, D.
abstract

A noisy database system is studied in which the noisy versions of the underlying feature vectors are observed in both the enrollment and the query phases. The noisy observations are compressed before being stored in the database, and the user wishes both to identify the correct entry corresponding to the noisy query vector and to reconstruct the original feature vector within a desired distortion requirement. A fundamental capacity/storage/distortion tradeoff is identified for this system in the form of single-letter information theoretic expressions. The relation of this problem to the classical Wyner-Ziv rate-distortion problem is shown, where the noisy query vector acts as the correlated side information in the lossy reconstruction of the feature vector. © 2010 IEEE.


2010 - Interference channels with correlated receiver side information [Articolo su rivista]
Liu, N.; Gunduz, D.; Goldsmith, A.; Poor, H. V.
abstract

The problem of joint source-channel coding in transmitting independent sources over interference channels with correlated receiver side information is studied. When each receiver has side information correlated with its own desired source, it is shown that source-channel separation is optimal. When each receiver has side information correlated with the interfering source, sufficient conditions for reliable transmission are provided based on a joint source-channel coding scheme using the superposition encoding and partial decoding idea of Han and Kobayashi. When the receiver side information is a deterministic function of the interfering source, source-channel separation is again shown to be optimal. In addition to these source-channel coding problems, a new channel model that generalizes the classical interference channel is introduced: the interference channel with message side information. Achievable rate regions are given and a single letter characterization of the capacity region for a special class of Z-interference channels is provided. Using this capacity result and the optimality of source-channel separation, we demonstrate that our sufficient conditions for reliable transmission when each receiver has side information correlated with the interfering source are also necessary for some special cases. As a by-product, the capacity region of a class of Z-channels with degraded message sets is also provided. © 2006 IEEE.


2010 - Multi-hop MIMO relay networks: Diversity-multiplexing trade-off analysis [Articolo su rivista]
Gunduz, D.; Khojastepour, M. A.; Goldsmith, A.; Poor, H. V.
abstract

A multi-hop relay network with multiple antenna terminals in a quasi-static slow fading environment is considered. The fundamental diversity-multiplexing gain tradeoff (DMT) is analyzed in the case of half-duplex relay terminals. While decodeand- forward (DF) relaying achieves the optimal DMT in the fullduplex relay scenario, it is shown that the dynamic decode-andforward (DDF) protocol achieves the optimal DMT if the relay is constrained to half-duplex operation. For the latter case, static DF protocols are considered as well, and the corresponding DMT performance is shown to fall short of the optimal performance, which indicates that dynamic channel allocation is required for optimal DMT performance. The optimal DMT is expressed as the solution of a convex optimization problem and explicit DMT expressions are presented for some special cases. In the case of multiple relays, it is shown that the optimal diversity gain, which is achieved by exploiting the available "hop-diversity", is dominated by the neighboring two-hops with the minimum diversity gain. © 2006 IEEE.


2010 - Multiple multicasts with the help of a relay [Articolo su rivista]
Gunduz, D.; Simeone, O.; Goldsmith, A. J.; Poor, H. V.; Shamai, S.
abstract

The problem of simultaneous multicasting of multiple messages with the help of a relay terminal is considered. In particular, a model is studied in which a relay station simultaneously assists two transmitters in multicasting their independent messages to two receivers. The relay may also have an independent message of its own to multicast. As a first step to address this general model, referred to as the compound multiple access channel with a relay (cMACr), the capacity region of the multiple access channel with a "cognitive" relay is characterized, including the cases of partial and rate-limited cognition. Then, achievable rate regions for the cMACr model are presented based on decode-and-forward (DF) and compress-and-forward (CF) relaying strategies. Moreover, an outer bound is derived for the special case, called the cMACr without cross-reception, in which each transmitter has a direct link to one of the receivers while the connection to the other receiver is enabled only through the relay terminal. The capacity region is characterized for a binary modulo additive cMACr without cross-reception, showing the optimality of binary linear block codes, and thus highlighting the benefits of physical layer network coding and structured codes. Results are extended to the Gaussian channel model as well, providing achievable rate regions for DF and CF, as well as for a structured code design based on lattice codes. It is shown that the performance with lattice codes approaches the upper bound for increasing power, surpassing the rates achieved by the considered random coding-based techniques. © 2006 IEEE.


2010 - On the capacity region of a multiple access channel with common messages [Relazione in Atti di Convegno]
Gunduz, D.; Simeone, O.
abstract

The capacity region for a multiple access channel (MAC) with arbitrary sets of common messages was derived by Han in 1979, extending a result by Slepian and Wolf from 1973. The general characterization by Han involves one auxiliary random variable per message and one inequality per subset of messages. In this paper, at first, a special hierarchy of common messages is identified for which the capacity region is characterized with generally fewer auxiliary random variables and inequalities. It is also shown that this characterization requires no auxiliary random variable for certain message structures. A procedure is then proposed to transform any common message structure to this special hierarchy, leading to a general capacity characterization which generally requires fewer auxiliary random variables than the one given by Han. © 2010 IEEE.


2010 - Outage capacity of bursty amplify-and-forward with incremental relaying [Relazione in Atti di Convegno]
Renk, T.; Jakel, H.; Jondral, F. K.; Gunduz, D.; Goldsmith, A.
abstract

We derive the outage capacity of a bursty version of the amplify-and-forward (BAF) protocol for small signal-to-noise ratios when incremental relaying is used. We show that the ratio between the outage capacities of BAF and the cut-set bound is independent of the relay position and that BAF is outage optimal for certain conditions on the target rate R. This is in contrast to decode-and-forward with incremental relaying, where the relay location strongly determines the performance of the cooperative protocol. We further derive the outage capacity for a network consisting of an arbitrary number of relay nodes. In this case the relays transmit in subsequent partitions of the overall transmission block and the destination accumulates signal-to-noise ratio until it is able to decode. © 2010 IEEE.


2010 - Source coding under secrecy constraints [Capitolo/Saggio]
Gunduz, D.; Erkip, E.; Poor, H. V.
abstract

Distributed compression involves compressing multiple data sources by exploiting the underlying correlation structure of the sources at separate non-cooperating encoders, while decoding is done jointly at a single decoder. Recent years have witnessed an increasing amount of research on the theoretical and practical aspects of distributed source codes, which find applications in distributed video compression, peer-to-peer data distribution systems, and sensor networks [1-3]. In many practical scenarios, limited network resources such as power and bandwidth, or physical limitations of the devices as in the case of sensor networks, pose challenges in terms of network performance and security. Oftentimes, the data aggregated in distributed compression systems may have commercial value as in the case of warehouse inventory monitoring systems, may contain sensitive information as in the case of distributed video surveillance systems, or might infringe personal privacy concerns as in the case of human body sensors measuring various health indicators. In all these scenarios, it is essential to develop distributed compression and communication protocols which exploit the limited power and bandwidth resources efficiently as well as satisfying the security requirements. Our goal in this chapter is to review fundamental limitations and tradeoffs for the overall performance optimization taking into account the quality and the security considerations jointly. There are two fundamental approaches to guarantee security in wireless networks. In the approach based on computational complexity [4], on which most practical cryptographic applications are based, the security of the system depends on the intractability assumption for a problem such as prime factorization. On the other hand, in the approach based on information theoretic secrecy introduced by Shannon in [5], the emphasis is on unconditional secrecy, which requires that, an eavesdropper with unbounded time and computational resources, and the knowledge of the encryption algorithm, does not gain any additional information about the underlying secret message upon intercepting the encrypted cryptogram. For a general review of recent progress in information theoretic security, see [6]. Although the complexity based approach has been successful in satisfying the security concerns of many practical networking applications such as the Internet, wireless networks pose additional limitations and threats that cannot be solved solely through encryption. The broadcast nature of the wireless medium makes it particularly vulnerable to eavesdropping and authentication attacks, and the energy and bandwidth limitations of wireless devices restrict their computational power, hence rendering high complexity encryption techniques undesirable. Furthermore, especially in the sensor network scenario, where the sensor nodes are generally deployed in remote locations highly vulnerable to tampering, secure key management becomes impractical. Issues such as mobility and lack of infrastructure (e.g., in mobile ad hoc networks) also pose significant challenges to traditional approaches based on maintaining secret keys. In such applications information theoretic security can support and enhance the computational complexity based approach. In this chapter, we survey information theoretic security in distributed source compression, and in particular how compression and communication can be achieved in an information theoretically secure way. Consider, for example, a sensor network in which correlated sensor observations are to be reconstructed at an access point either in a lossless fashion or within a prescribed distortion requirement. While some sensors might have secure (possibly wired) connections to the access point, others might be transmitting over the wireless medium, which can be accessed by an adversary trying to obtain information about the underlying phenomenon. Furthermore, this adversary might have her


2010 - Successive refinement of vector sources under individual distortion criteria [Articolo su rivista]
Nayak, J.; Tuncel, E.; Gunduz, D.; Erkip, E.
abstract

The successive refinement problem is extended to vector sources where individual distortion constraints are posed on each vector component. For vector Gaussian sources with squared-error distortion, a single-letter rate-distortion characterization is inherited from the previously studied Gaussian multiple descriptions problem with covariance distortion constraints. Though this characterization is amenable to well-known numerical convex optimization techniques, an analytical solution is difficult to obtain in full generality even for 2-D sources. In this work, the special case of successive refinability is addressed analytically. Specifically, vector Gaussian sources are shown to be not successively refinable everywhere unlike scalar Gaussian sources. It is also shown that, for 2-D Gaussian sources, the rate loss at the second stage can be as high as 0.5 b/sample in a degenerate scenario corresponding to what is known as sequential coding of correlated sources. Finally, analysis of 2-D binary symmetric sources with Hamming distortion reveals that the behavior of these sources with respect to successive refinability exhibits remarkable similarity to their 2-D Gaussian counterparts. © 2006 IEEE.


2010 - Wyner-Ziv coding over broadcast channels: Digital schemes [Articolo su rivista]
Nayak, J.; Tuncel, E.; Gunduz, D.
abstract

This paper addresses lossy transmission of a common source over a broadcast channel when there is correlated side information at the receivers, with emphasis on the quadratic Gaussian and binary Hamming cases. A digital scheme that combines ideas from the lossless version of the problem, i.e., SlepianWolf coding over broadcast channels, and dirty paper coding, is presented and analyzed. This scheme uses layered coding where the common layer information is intended for both receivers and the refinement information is destined only for one receiver. For the quadratic Gaussian case, a quantity characterizing the combined quality of each receiver is identified in terms of channel and side information parameters. It is shown that it is more advantageous to send the refinement information to the receiver with better combined quality. In the case where all receivers have the same overall quality, the presented scheme becomes optimal. Unlike its lossless counterpart, however, the problem eludes a complete characterization. © 2006 IEEE.


2009 - Compound multiple-access channels with partial cooperation [Articolo su rivista]
Simeone, O.; Gunduz, D.; Poor, H. V.; Goldsmith, A. J.; Shamai (Shitz), S.
abstract

A two-user discrete memoryless compound multiple-access channel (MAC) with a common message and conferencing decoders is considered. The capacity region is characterized in the special cases of physically degraded channels and unidirectional cooperation, and achievable rate regions are provided for the general case. The results are then extended to the corresponding Gaussian model. In the Gaussian setup, the provided achievable rates are shown to lie within some constant number of bits from the boundary of the capacity region in several special cases. An alternative model, in which the encoders are connected by conferencing links rather than having a common message, is studied as well, and the capacity region for this model is also determined for the cases of physically degraded channels and unidirectional cooperation. Numerical results are also provided to obtain insights about the potential gains of conferencing at the decoders and encoders. © 2009 IEEE.


2009 - Compound relay channel with informed relay and destination [Relazione in Atti di Convegno]
Simeone, O.; Gunduz, D.; Shamai (Shitz), S.
abstract

A two-state compound relay channel is considered where the relay and the destination are informed about the channel state while the source is not. Achievable rates and upper bounds are derived for discrete memoryless and Gaussian models, and specialized to a scenario with orthogonal components. It is shown that, apart from some special cases, optimality conditions valid for decode-and-forward (DF)-based solutions on a standard relay channel do not carry over to a compound setting, and more fl exible transmission strategies are generally advantageous. For instance, partial decode-and-forward (PDF) that superimposes transmission of three layers and uses joint decoding at the destination performs better than the standard two-layer PDF with successive decoding, even when the latter is optimal for the regular relay channel. Moreover, the capacity is derived in the special case in which the relay is not active in one state. Extension to the broadcast coding approach, as an alternative to the compound model, is also discussed. ©2009 IEEE.


2009 - Distortion exponent in MIMO channels with feedback [Relazione in Atti di Convegno]
Gunduz, D.; Goldsmith, A. J.; Poor, H. V.
abstract

The transmission of a Gaussian source over a blockfading multiple antenna channel in the presence of a feedback link is considered. The feedback link is assumed to be an error and delay free link of capacity 1 bit per channel use. Under the short-term power constraint, the optimal exponential behavior of the end-to-end average distortion is characterized for all source-channel bandwidth ratios. It is shown that the optimal transmission strategy is successive refinement source coding followed by progressive transmission over the channel, in which the channel block is allocated dynamically among the layers based on the channel state using the feedback link as an instantaneous automatic repeat request (ARQ) signal. © 2009 IEEE.


2009 - Distortion minimization in Gaussian layered broadcast coding with successive refinement [Articolo su rivista]
Ng, C. T. K.; Gunduz, D.; Goldsmith, A. J.; Erkip, E.
abstract

A transmitter without channel state information wishes to send a delay-limited Gaussian source over a slowly fading channel. The source is coded in superimposed layers, with each layer successively refining the description in the previous one. The receiver decodes the layers that are supported by the channel realization and reconstructs the source up to a distortion. The expected distortion is minimized by optimally allocating the transmit power among the source layers. For two source layers, the allocation is optimal when power is first assigned to the higher layer up to a power ceiling that depends only on the channel fading distribution; all remaining power, if any, is allocated to the lower layer. For convex distortion cost functions with convex constraints, the minimization is formulated as a convex optimization problem. In the limit of a continuum of infinite layers, the minimum expected distortion is given by the solution to a set of linear differential equations in terms of the density of the fading distribution. As the number of channel uses per source symbol tends to zero, the power distribution that minimizes expected distortion converges to the one that maximizes expected capacity. © 2009 IEEE.


2009 - Identification over multiple databases [Relazione in Atti di Convegno]
Gunduz, D.; Tuncel, E.; Goldsmith, A.; Poor, V.
abstract

The tradeoff between storage and identification rates for multiple databases is investigated from an information theoretic perspective. In the assumed model, noisy observations of feature vectors of two distinct groups, called the ancestors, are compressed and stored in two separate databases. When queried with a noisy observation of a (possibly random) function of two randomly selected ancestors (one from each group), the system is required to correctly identify the ancestors with high probability. Single-letter inner and outer bounds are presented on the set of achievable rate points, which identify a tradeoff between the compression rates and the identification rate region: the lower the compression rates for storage, the larger the rate region achievable for identification. © 2009 IEEE.


2009 - Outage capacity of incremental relaying at low signal-to-noise ratios [Relazione in Atti di Convegno]
Renk, T.; Jakel, H.; Jondral, F. K.; Gunduz, D.; Goldsmith, A.
abstract

We present the ε-outage capacity of incremental relaying at low signal-to-noise ratios (SNR) in a wireless cooperative network with slow Rayleigh fading channels. The relay performs decode-and-forward and repetition coding is employed in the network, which is optimal in the low SNR regime. We derive an expression on the optimal relay location that maximizes the ε-outage capacity. It is shown that this location is independent of the outage probability and SNR but only depends on the channel conditions represented by a path-loss factor. We compare our results to the ε-outage capacity of the cut-set bound and demonstrate that the ratio between the ε-outage capacity of incremental relaying and the cut-set bound lies within 1/ √ 2 and 1. Furthermore, we derive lower bounds on the ε-outage capacity for the case of K relays. © 2009 IEEE.


2009 - Relaying simultaneous multicasts via structured codes [Relazione in Atti di Convegno]
Gunduz, D.; Simeone, O.; Goldsmith, A. J.; Poor, H. V.; Shamai, S.
abstract

Simultaneous multicasting of messages with the help of a relay is studied. A two-source two-destination network is considered, in which each destination can receive directly only the signal from one of the sources, so that the reception of the message from the other source (and multicasting) is enabled by the presence of the relay. An outer bound is derived which is shown to be achievable in the case of finite-field moduloadditive channels by using linear codes, highlighting the benefits of structured codes in exploiting the underlying physical-layer structure of the network. Results are extended to the Gaussian channel model as well, providing achievable rate regions based on nested lattice codes. It is shown that for a wide range of power constraints, the performance with lattice codes approaches the upper bound and surpasses the rates achieved by the standard random coding schemes. © 2009 IEEE.


2009 - Source and channel coding for correlated sources over multiuser channels [Articolo su rivista]
Gunduz, D.; Erkip, E.; Goldsmith, A.; Poor, H. V.
abstract

Source and channel coding over multiuser channels in which receivers have access to correlated source side information are considered. For several multiuser channel models necessary and sufficient conditions for optimal separation of the source and channel codes are obtained. In particular, the multiple-access channel, the compound multiple-access channel, the interference channel, and the two-way channel with correlated sources and correlated receiver side information are considered, and the optimality of separation is shown to hold for certain source and side information structures. Interestingly, the optimal separate source and channel codes identified for these models are not necessarily the optimal codes for the underlying source coding or the channel coding problems. In other words, while separation of the source and channel codes is optimal, the nature of these optimal codes is impacted by the joint design criterion. © 2009 IEEE.


2008 - Compound multiple access channels with conferencing decoders [Relazione in Atti di Convegno]
Simeone, O.; Gunduz, D.; Goldsmith, A. J.; Poor, H. V.; Shamai, S.
abstract

A two-user discrete memoryles ple access channel with a common messag decoders is considered. The capacity regio in the special cases of physically degra unidirectional cooperation, while achievabl provided for the general case. The results to the corresponding Gaussian model. In t the provided achievable rates are shown to l of one bit from the boundary of the capaci special cases. Numerical results are also insights about the potential gains of decoder underlying model. © 2008 IEEE.


2008 - Diversity-multiplexing tradeoffs in MIMO relay channels [Relazione in Atti di Convegno]
Gunduz, D.; Goldsmith, A.; Poor, H. V.
abstract

A multi-hop relay channel with multiple antenna terminals in a quasi-static slow fading environment is considered. For both full-duplex and half-duplex relays the fundamental diversity-multiplexing tradeoff (DMT) is analyzed. It is shown that, while decode-and-forward (DF) relaying achieves the optimal DMT in the full-duplex relay scenario, the dynamic decode and-forward (DDF) protocol is needed to achieve the optimal DMT if the relay is constrained to half-duplex operation. For the latter case, static protocols are considered as well, and the corresponding achievable DMT performance is characterized. © 2008 IEEE.


2008 - Joint source-channel codes for MIMO block-fading channels [Articolo su rivista]
Gunduz, D.; Erkip, E.
abstract

We consider transmission of a continuous amplitude source over an L-block Rayleigh-fading Mt × Mr multiple-input multiple-output (MIMO) channel when the channel state information is only available at the receiver. Since the channel is not ergodic, Shannon's source-channel separation theorem becomes obsolete and the optimal performance requires a joint source-channel approach. Our goal is to minimize the expected end-to-end distortion, particularly in the high ignal-to-noise ratio (SNR) regime. The figure of merit is the distortion exponent, de-fined as the exponential decay rate of the expected distortion with increasing SNR. We provide an upper bound and lower bounds for the distortion exponent with respect to the bandwidth ratio among the channel and source bandwidths. For the lower bounds, we analyze three different strategies based on layered source coding concatenated with progressive superposition or hybrid digital/analog transmission. In each case, by adjusting the system parameters we optimize the distortion exponent as a function of the bandwidth ratio. We prove that the distortion exponent upper bound can be achieved when the channel has only one degree of freedom, that is L = 1, and min {Mt, Mr} = 1. When we have more degrees of freedom, our achievable distortion exponents meet the upper bound for only certain ranges of the bandwidth ratio. We demonstrate that our results, which were derived for a complex Gaussian source, can be extended to more general source distributions as well. © 2008 IEEE.


2008 - Lossless compression with security constraints [Relazione in Atti di Convegno]
Gunduz, D.; Erkip, E.; Poor, H. V.
abstract

Secure distributed data compression in the presence of an eavesdropper is explored. Two correlated sources that need to be reliably transmitted to a legitimate receiver are available at separate encoders. Noise-free, limited rate links from the encoders to the legitimate receiver, one of which can also be perfectly observed by the eavesdropper, are considered. The eavesdropper also has its own correlated observation. Inner and outer bounds on the achievable compression-equivocation rate region are given. Several different scenarios involving the side information at the transmitters as well as multiple receivers/eavesdroppers are also considered. © 2008 IEEE.


2008 - Lossy source transmission over the relay channel [Relazione in Atti di Convegno]
Gunduz, D.; Erkip, E.; Goldsmith, A.; Poor, H. V.
abstract

Lossy transmission over a relay channel in which the relay has access to correlated side information is considered. First, a joint source-channel decode-and-forward scheme is proposed for general discrete memoryless sources and channels. Then the Gaussian relay channel where the source and the side information are jointly Gaussian is analyzed. For this Gaussian model, several new source-channel cooperation schemes are introduced and analyzed in terms of the squared-error distortion at the destination. A comparison of the proposed upper bounds with the cut-set lower bound is given, and it is seen that joint source-channel cooperation improves the reconstruction quality significantly. Moreover, the performance of the joint code is close to the lower bound on distortion for a wide range of source and channel parameters. © 2008 IEEE.


2008 - MIMO two-way relay channel: Diversity-multiplexing tradeoff analysis [Relazione in Atti di Convegno]
Gunduz, D.; Goldsmith, A.; Poor, H. V.
abstract

A multi-hop two-way relay channel is considered in which all the terminals are equipped with multiple antennas. Assuming independent quasi-static Rayleigh fading channels and channel state information available at the receivers, we characterize the optimal diversity-multiplexing gain tradeoff (DMT) curve for a full-duplex relay terminal. It is shown that the optimal DMT can be achieved by a compress-and-forward type relaying strategy in which the relay quantizes its received signal and transmits the corresponding channel codeword. It is noteworthy that, with this transmission protocol, the two transmissions in opposite directions can achieve their respective single user optimal DMT performances simultaneously, despite the interference they cause to each other. Motivated by the optimality of this scheme in the case of the two-way relay channel, a novel dynamic compress-and-forward (DCF) protocol is proposed for the one-way multi-hop MIMO relay channel for a half-duplex relay terminal, and this scheme is shown to achieve the optimal DMT performance. © 2008 IEEE.


2008 - Rate regions for the separated two-way relay channel [Relazione in Atti di Convegno]
Gunduz, D.; Tuncel, E.; Nayak, J.
abstract

A two-way relay channel in which two users communicate with each other over a relay terminal is considered. In particular, a "separated" two-way relay channel, in which the users do not receive each other's signals is studied. Various achievable schemes are proposed and corresponding achievable rate regions are characterized. Specifically, a combination of partial decode-and-forward and compress-and-forward schemes is proposed. In addition, compress-and-forward relaying with two layered quantization, in which one of the users receive a better description of the relay received signal is studied. Extension of these achievable schemes to the Gaussian separated two-way relay channel is presented. It is shown that the compress-and-forward scheme achieves rates within half bit of the capacity region in the Gaussian setting. Numerical results are also presented for comparison of the proposed achievable schemes in the Gaussian case. © 2008 IEEE.


2008 - Resource allocation for cooperative relaying [Relazione in Atti di Convegno]
Yang, J.; Gunduz, D.; Brown, R.; Erkip, E.
abstract

The delay-limited capacity of the half-duplex relay channel is analyzed for several cooperative protocols under a long-term average total transmit power constraint. It is assumed that the source and the relay have access to partial channel state information in the form of channel amplitudes. Nonorthogonal amplify-and-forward (NAF), compress-and-forward (CF) and opportunistic decode-and-forward (ODF) protocols are compared with optimal resource allocation, i.e., at each channel state, the source and the relay transmit with the minimum total power allocation required to achieve the target rate. A hybrid opportunistic protocol is proposed in which CF or ODF with optimal resource allocation is chosen at each channel state. Numerical results demonstrate that, while the hybrid protocol offers the best delay-limited capacity, ODF follows the hybrid scheme closely for a wide range of relay locations and average power constraints. We also consider various low complexity protocols such as fixed time allocation and the estimate-andforward (EF) protocol in order to analyze the trade-off between the system complexity and delay-limited capacity. © 2008 IEEE.


2008 - Secret communication with feedback [Relazione in Atti di Convegno]
Gunduz, D.; Brown, R.; Poor, H. V.
abstract

Secure communication with feedback is studied. An achievability scheme in which the backward channel is used to generate a shared secret key is proposed. The scenario of binary symmetric forward and backward channels is considered, and a combination of the proposed scheme and Maurer's coding scheme is shown to achieve improved secrecy rates. The scenario of a Gaussian channel with perfect output feedback is also analyzed and the Schalkwijk-Kailath coding scheme is shown to achieve the secrecy capacity for this channel.


2008 - Wyner-Ziv coding over broadcast channels [Relazione in Atti di Convegno]
Nayak, J.; Tuncel, E.; Gunduz, D.
abstract

This paper deals with the design of coding schemes for lossy transmission of a source over a broadcast channel when there is correlated side information at the receivers. Using ideas from Slepian-Wolf coding over broadcast channels and dirty paper coding, new schemes are presented and their rate-distortion performance is derived. For the binary Hamming and quadratic Gaussian scenarios, when the source and the channel bandwidths are equal, it is shown that these schemes are sometimes optimal and that they can outperform both separate source and channel coding, and uncoded transmission. ©2008 IEEE.


2008 - Wyner-Ziv coding over broadcast channels using hybrid digital/analog transmission [Relazione in Atti di Convegno]
Gunduz, D.; Nayak, J.; Tuncel, E.
abstract

This paper deals with the design of coding schemes for transmitting a source over a broadcast channel when there is source side information at the receivers. Based on Slepian-Wolf coding over broadcast channels, three hybrid digital/analog schemes are proposed and their power-distortion tradeoff is investigated for Gaussian sources and Gaussian broadcast channels. All three transmit the same digital and analog information but with varying coding order. Although they are not provably optimal in general, they can significantly outperform uncoded transmission and separate source and channel coding. © 2008 IEEE.


2007 - Cooperative source and channel coding for wireless multimedia communications [Articolo su rivista]
Shutoy, H.; Gunduz, D.; Erkip, E.; Wang, Y.
abstract

Past work on cooperative communications has indicated substantial improvements in channel reliability through cooperative transmission strategies. To exploit cooperation benefits for multimedia transmission over slow fading channels, we propose to jointly allocate bits among source coding, channel coding and cooperation to minimize the expected distortion of the reconstructed signal at the receiver. Recognizing that, not all source bits are equally important in terms of the end-to-end distortion, we further propose to protect the more important bits through user cooperation. We compare four modes of transmission that differ in their compression and error protection strategies (single layer or multiple layer source coding with unequal error protection, with versus without cooperation). Our study includes an i.i.d. Gaussian source as well as a video source employing an H.263+ codec. We present an information theoretic analysis for the Gaussian source to investigate the effects of the modulation scheme, bandwidth ratio (number of channel uses per source sample), and average link signal-to-noise ratios on the end-to-end distortion of the four modes studied. The information theoretic observations are validated using practical channel coding simulations. Our study for video considers error propagation in decoded video due to temporal prediction and jointly optimizes a source coding parameter that controls error propagation, in addition to bits for source coding, channel coding and cooperation. The results show that cooperation can significantly reduce the expected end-to-end distortion for both types of source and that layered cooperation provides further improvements and extends the benefits to a wider range of channel qualities. © 2007 IEEE.


2007 - Correlated sources over an asymmetric multiple access channel with one distortion criterion [Relazione in Atti di Convegno]
Gunduz, D.; Erkip, E.
abstract

We consider transmission of two arbitrarily correlated sources over a discrete memoryless asymmetric multiple access channel, where one of the sources is available at both transmitters. We want to transmit the common source lossless in the Shannon sense, while there is a distortion requirement on the other source. For a given bandwidth ratio between the channel and source bandwidths and a distortion requirement, we derive the necessary and sufficient conditions, and show that separation of source and channel coding is optimal. Finally, we extend our results to the case where perfect casual feedback is available at either one or both of the transmitters. © 2007 IEEE.


2007 - Dynamic resource allocation for the broadband relay channel [Relazione in Atti di Convegno]
Bakanoglu, K.; Gunduz, D.; Erkip, E.
abstract

We consider a half-duplex broadband relay channel which is composed of L parallel, independent Rayleigh fading relay channels. Partial channel state information in the form of channel state amplitudes is available at the transmitters while the receivers have perfect channel state information. We assume a long term total average power constraint at the source and the relay. We dynamically allocate the power and the relay transmission time to improve the delay limited capacity or alternatively to decrease the outage probability. We analyze multi-hop (MH) and opportunistic decodeand-forward (ODF) protocols for the broadband relay channel and propose various subchannel resource allocation strategies. Simulation based performance comparisons also include the modified cut-set bound. © 2007 IEEE.


2007 - Lossless transmission of correlated sources over a multiple access channel with side information [Relazione in Atti di Convegno]
Gunduz, D.; Erkip, E.
abstract

In this paper, we consider lossless transmission of arbitrarily correlated sources over a multiple access channel. Characterization of the achievable rates in the most general setting is one of the longstanding open problems of information theory. We consider a special case of this problem where the receiver has access to correlated side information given which the sources are independent. We prove a source channel separation theorem for this system, that is, we show that there is no loss in performance in first applying distributed source coding where each encoder compresses its source conditioned on the side information at the receiver, and then applying an optimal multiple access channel code with independent codebooks. We also give necessary and sufficient conditions for source and channel separability in the above problem if there is perfect two-sided feedback from the receiver to the transmitters. These two communication scenarios constitute examples of few non-trivial multi-user scenarios for which separation holds. © 2007 IEEE.


2007 - Minimum expected distortion in Gaussian layered broadcast coding with successive reinement [Relazione in Atti di Convegno]
Ng, T. K.; Gunduz, D.; Goldsmith, A. J.; Erkip, E.
abstract

A transmitter without channel state information (CSI) wishes to send a delay-limited Gaussian source over a slowly fading channel. The source Is coded in superimposed layers, with each layer successively refining the description in the previous one. The receiver decodes the layers that arc supported by the channel realization and reconstructs the source up to a distortion. In the limit of a continuum of infinite layers, the optimal power distribution thai minimizes the expected distortion is given by the solution to a set of linear differential equations in terms of the density of the fading distribution. In the optimal power distribution, as SNR increases, the allocation over the higher layers remains unchanged; rather the extra power is allocated towards the lower layers. On the other hand, as the bandwidth ratio b (channel uses per source symbol) tends to zero, the power distribution that minimizes expected distortion converges to the power distribution that maximizes expected capacity. While expected distortion can be improved by acquiring CSI at the transmitter (CSIT) or by increasing diversity from the realization of independent fading paths, at high SNR the performance benefit from diversity exceeds that from CSIT, especially when b is large. ©2007 IEEE.


2007 - Opportunistic cooperation by dynamic resource allocation [Articolo su rivista]
Gunduz, D.; Erkip, E.
abstract

We consider a Rayleigh fading wireless relay channel where communication is constrained by delay and average power limitations. Assuming partial channel state information at the transmitters and perfect channel state information at the receivers, we first study the delay-limited capacity of this system and show that, contrary to a single source-single destination case, a non-zero delay-limited capacity is achievable. We introduce opportunistic decode-and-forward (ODF) protocol which utilizes the relay depending on the channel state. Opportunistic cooperation significantly improves the delay-limited capacity of the system and performs very close to the cut-set bound. We also consider the system performance in terms of minimum outage probability. We show that ODF provides performance close to the cut-set bound from the outage probability perspective as well. Our results emphasize the importance of feedback for cooperative systems that have delay sensitive applications. © 2007 IEEE.


2007 - Recursive power allocation in gaussian layered broadcast coding with successive refinement [Relazione in Atti di Convegno]
Ng, T. K.; Gunduz, D.; Goldsmith, A. J.; Erkip, E.
abstract

A transmitter without channel state information wishes to send a delay-limited Gaussian source over a slowly fading channel that has a finite number of discrete fading states. The source is coded in layers, with each layer successively refining the description in the previous one. These coded source layers are then superimposed and simultaneously transmitted to the receiver. The receiver decodes the layers that are supported by the realization of the channel, and combines the descriptions in the decoded layers to reconstruct the source up to a distortion. The expected distortion is minimized by optimally allocating the transmit power among the given number of source layers. For two layers, the allocation is optimal when power is first assigned to the higher layer up to a power ceiling that depends only on the channel fading distribution; all remaining power, if any, is allocated to the lower layer. For multiple layers, the overall expected distortion can be written as a set of recurrence relations, and the minimum expected distortion is found by recursively applying the two-layer optimization procedure at each recurrence step. ©2007 IEEE.


2007 - Reliable cooperative source transmission with side information [Relazione in Atti di Convegno]
Gunduz, D.; Erkip, E.
abstract

We consider reliable transmission of a discrete memoryless source over a cooperative relay broadcast channel, where both the relay and the destination terminals want to reconstruct the source; and over a relay channel, where only the destination terminal wishes to obtain a lossless reconstruction. We assume that both the relay and the destination have correlated side information. We find the necessary and sufficient conditions for a general cooperative relay broadcast channel, and for a physically degraded relay channel when the side information at the destination is a degraded version of the relay side information. Our achievability results are based on operational source-channel separation. We utilize source and channel codes that interact only by passing along decoded source codewords from one block to another. ©2007 IEEE.


2007 - Source and channel coding for cooperative relaying [Articolo su rivista]
Gunduz, D.; Erkip, E.
abstract

User cooperation is a powerful tool to combat fading and increase robustness for communication over wireless channels. Although it is doubtless a promising technique for enhancing channel reliability, its performance in terms of average source distortion is not clear since source-channel separation theorem fails under the most common nonergodic slow-fading channel assumption, when channel state information (CSI) is only available at the receiving terminals. This work sheds some light on the end-to-end performance of joint source-channel coding for cooperative relay systems in the high signal-to-noise ratio (SNR) regime. Considering distortion exponent as a figure of merit, we propose various strategies for cooperative source and channel coding that significantly improve the performance compared to the conventional scheme of source coding followed by cooperative channel coding. We characterize the optimal distortion exponent of a full-duplex relay channel for all bandwidth ratios. For the half-duplex relay channel, we provide an upper bound which is tight for small and large bandwidth ratios. We consider the effect of correlated side information on the distortion exponent as well. © 2007 IEEE.


2007 - Successive refinement of vector sources under individual distortion criteria [Relazione in Atti di Convegno]
Nayak, J.; Tuncel, E.; Gunduz, D.; Erkip, E.
abstract

The well-known successive refinement scenario is extended to vector sources where individual distortion constraints are posed on every vector component. This extension is then utilized for the derivation of a necessary and sufficient condition for vector successive refinability. For 2-D vector Gaussian and binary symmetric sources, it turns out that successive refinability is not granted everywhere, unlike in the 1-D case for the same sources. Moreover, the behavior of these sources with respect to successive refinability exhibit remarkable similarity. © 2007 IEEE.


2006 - Distortion exponent of MIMO fading channels [Relazione in Atti di Convegno]
Gunduz, D.; Erkip, E.
abstract

In this paper, we consider transmission of a continuous amplitude source over a quasi-static MIMO Rayleigh fading channel. The performance metric is end-to-end distortion of the source caused both by the lossy compression and the channel errors. We are interested in the high SNR behavior expressed in the distortion exponent, which is the exponential decay rate of the average end-to-end distortion as a function of SNR. Our goal is to maximize this distortion exponent by considering joint source and channel coding techniques. We provide digital strategies that utilize layered source coding coupled with multi-rate channel coding either by progressive or by superposition transmission, as well as a hybrid digital-analog scheme. When either the transmitter or the receiver has one antenna, we show that we are able to achieve the optimal distortion exponent. © 2006 IEEE.


2006 - Distortion exponent of parallel fading channels [Relazione in Atti di Convegno]
Gunduz, D.; Erkip, E.
abstract

We consider the end-to-end distortion achieved by transmitting a continuous amplitude source over M parallel, independent quasi-static fading channels. We analyze the high SNR expected distortion behavior characterized by the distortion exponent. We first give an upper bound for the distortion exponent in terms of the bandwidth ratio between the channel and the source assuming the availability of the channel state information at the transmitter. Then we propose joint source-channel coding schemes based on layered source coding and multiple rate channel coding. We show that the upper bound is tight for large and small bandwidth ratios. For the rest, we provide the best known distortion exponents in the literature. By suitably scaling the bandwidth ratio, our results would also apply to block fading channels. © 2006 IEEE.


2005 - Layered cooperative source and channel coding [Relazione in Atti di Convegno]
Xu, X.; Gunduz, D.; Erkip, E.; Wang, Y.
abstract

Cooperative techniques form a new wireless communication paradigm in which terminals help each other in relaying information to combat the random fading and to provide diversity in radio channels. Past work has focused on improving channel reliability through cooperation. We propose to jointly allocate bits among source coding, channel coding and cooperation to minimize the expected source distortion. Recognizing that not all source bits are equal, we further propose to protect the more important bits through user cooperation. To evaluate the gain of layered cooperation, we simulate four modes of communications that differ in their error protection strategy (equal vs. layered, with vs. without cooperation) with a practical channel coder, and show that, for i.i.d. Gaussian sources, layered cooperation can achieve significant performance gains over non-layered/non-cooperative communication. We also carry out an information theoretic analysis illustrating fundamental benefits of layered cooperation. © 2005 IEEE.


2005 - Outage minimization by opportunistic cooperation [Relazione in Atti di Convegno]
Gunduz, D.; Erkip, E.
abstract

We consider a wireless relay network where communication is constrained by delay and average power limitations. We assume that partial channel state information is available at the transmitters while the receivers have the perfect channel state information, and consider the system performance in terms of outage probability. We propose an opportunistic user cooperation protocol that utilizes the channel state information to decide when and how to cooperate. We show that compared to fixed type cooperation schemes, our protocol improves the outage performance significantly and performs very close to the half-duplex lower bound while reducing the resources used by the relay. © 2005 IEEE.


2005 - Source and channel coding for cooperative relaying [Relazione in Atti di Convegno]
Gunduz, D.; Erkip, E.
abstract

We consider the end-to-end distortion achieved by a half-duplex relay system where a continuous amplitude source is transmitted over a quasi-static Rayleigh fading channel. We investigate layered source coding (LS) where different source layers are sent at different times. The relay only forwards the important layers, leading to higher multiplexing gains. Alternatively, different source layers can be superimposed using a broadcast code (BS). The third strategy we consider is uncoded transmission (UT) followed by amplify-and-forward relaying. In all cases we perform a high S N R analysis and find the optimal distortion exponent which is the exponential decay rate of expected distortion with increasing S N R. We show that layered compression and broadcast coding is optimal in distortion exponent sense for large bandwidth expansions: © 2005 IEEE.


2005 - Source and channel coding for quasi-static fading channels [Relazione in Atti di Convegno]
Gunduz, D.; Erkip, E.
abstract

We consider transmission of a continuous amplitude source over a quasi-static Rayleigh fading channel. We analyze three different source and channel coding strategies in terms of overall expected distortion (ED). Our goal is to maximize the distortion exponent (A), which is the exponential decay rate of ED with increasing S N R. In each case, by adjusting the system parameters we find the best A as a function of the bandwidth expansion. We also find an upper bound for A and illustrate how this upper bound can be achieved for all bandwidth expansions even with reasonably simple strategies. Although we focus on a Gaussian source for brevity, we demonstrate that our results can be extended to more general source distributions. © 2005 IEEE.


2004 - Joint source-channel cooperation: Diversity versus spectral efficiency [Relazione in Atti di Convegno]
Gunduz, D.; Erkip, E.
abstract

User cooperation is a spatial diversity technique where multiple terminals form a virtual antenna array to combat fading. We incorporate source coding into the cooperation scenario and analyze cooperation protocols with respect to the average distortion they achieve. We first compare the amplify-and-forward (AF) protocol to direct transmission (DT) and show that it does not increase the performance in the average distortion sense. Then we propose two new cooperation protocols which achieve better performance by increasing the spectral efficiency while still providing diversity, yet maintaining the simple nature of the previous protocols.