Imperial College London

DrDenizGunduz

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Reader in Information Theory and Communications
 
 
 
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Contact

 

+44 (0)20 7594 6218d.gunduz Website

 
 
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Assistant

 

Ms Joan O'Brien +44 (0)20 7594 6316

 
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Location

 

1016Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
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185 results found

Tung T-Y, Gunduz D, 2018, SparseCast: Hybrid Digital-Analog Wireless Image Transmission Exploiting Frequency-Domain Sparsity, IEEE COMMUNICATIONS LETTERS, Vol: 22, Pages: 2451-2454, ISSN: 1089-7798

JOURNAL ARTICLE

Giaconi G, Gunduz D, Poor HV, 2018, Privacy-Aware Smart Metering Progress and challenges, IEEE SIGNAL PROCESSING MAGAZINE, Vol: 35, Pages: 59-78, ISSN: 1053-5888

JOURNAL ARTICLE

Rassouli B, Varasteh M, Gunduz D, 2018, Gaussian multiple access channels with one-bit quantizer at the receiver, Entropy, Vol: 20, ISSN: 1099-4300

The capacity region of a two-transmitter Gaussian multiple access channel(MAC) under average input power constraints is studied, when the receiveremploys a zero-threshold one-bit analog-to-digital converter (ADC). It isproved that the input distributions of the two transmitters that achieve theboundary points of the capacity region are discrete. Based on the position of aboundary point, upper bounds on the number of the mass points of thecorresponding distributions are derived.

JOURNAL ARTICLE

Shi J, Liu L, Gunduz D, Ling Cet al., 2018, Polar Codes and Polar Lattices for the Heegard-Berger Problem, IEEE TRANSACTIONS ON COMMUNICATIONS, Vol: 66, Pages: 3760-3771, ISSN: 0090-6778

JOURNAL ARTICLE

Guler B, Gunduz D, Yener A, 2018, Lossy Coding of Correlated Sources Over a Multiple Access Channel: Necessary Conditions and Separation Results, IEEE TRANSACTIONS ON INFORMATION THEORY, Vol: 64, Pages: 6081-6097, ISSN: 0018-9448

JOURNAL ARTICLE

Rassouli B, Gunduz D, 2018, On Perfect Privacy, Pages: 2551-2555, ISSN: 2157-8095

© 2018 IEEE. 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

CONFERENCE PAPER

Amiri MM, Gunduz D, 2018, Caching and Coded Delivery Over Gaussian Broadcast Channels for Energy Efficiency, IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, Vol: 36, Pages: 1706-1720, ISSN: 0733-8716

JOURNAL ARTICLE

Ceran ET, Gunduz D, Gyorgy A, 2018, Average age of information with hybrid ARQ under a resource constraint, Wireless Communications and Networking Conference (WCNC), Publisher: IEEE, ISSN: 1525-3511

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.

CONFERENCE PAPER

Somuyiwa SO, Gyorgy A, Gunduz D, 2018, A Reinforcement-Learning Approach to Proactive Caching in Wireless Networks, IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, Vol: 36, Pages: 1331-1344, ISSN: 0733-8716

JOURNAL ARTICLE

Yang Q, Gunduz D, 2018, Coded Caching and Content Delivery With Heterogeneous Distortion Requirements, IEEE TRANSACTIONS ON INFORMATION THEORY, Vol: 64, Pages: 4347-4364, ISSN: 0018-9448

JOURNAL ARTICLE

Bharath BN, Nagananda KG, Gunduz D, Poor HVet al., 2018, Caching With Time-Varying Popularity Profiles: A Learning-Theoretic Perspective, IEEE Transactions on Communications, ISSN: 0090-6778

IEEE 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 profile, 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 β-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.

JOURNAL ARTICLE

Ozfatura E, Gunduz D, 2018, Mobility and Popularity-Aware Coded Small-Cell Caching, IEEE COMMUNICATIONS LETTERS, Vol: 22, Pages: 288-291, ISSN: 1089-7798

JOURNAL ARTICLE

Sreekumar S, Gunduz D, 2018, Testing Against Conditional Independence Under Security Constraints, IEEE International Symposium on Information Theory (ISIT), Publisher: IEEE, Pages: 181-185

CONFERENCE PAPER

Cao D, Zhang D, Chen P, Liu N, Kang W, Gunduz Det al., 2018, Coded Caching with Heterogeneous Cache Sizes and Link Qualities: The Two-User Case, IEEE International Symposium on Information Theory (ISIT), Publisher: IEEE, Pages: 1545-1549

CONFERENCE PAPER

Amiri MM, Gunduz D, 2018, On the Capacity Region of a Cache-Aided Gaussian Broadcast Channel with Multi-Layer Messages, IEEE International Symposium on Information Theory (ISIT), Publisher: IEEE, Pages: 1909-1913

CONFERENCE PAPER

, 2018, Polar codes and polar lattices for the heegard-berger problem, Pages: 100-105

© 2018 VDE VERLAG GMBH. 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.

CONFERENCE PAPER

Roushdy A, Motahari AS, Nafie M, Gunduz Det al., 2018, Cache-Aided Fog Radio Access Networks with Partial Connectivity, IEEE Wireless Communications and Networking Conference (WCNC), Publisher: IEEE, ISSN: 1525-3511

CONFERENCE PAPER

Mital N, Gunduz D, Ling C, 2018, Coded Caching in a Multi-Server System with Random Topology, IEEE Wireless Communications and Networking Conference (WCNC), Publisher: IEEE, ISSN: 1525-3511

CONFERENCE PAPER

Coon JP, Badiu M-A, Gunduz D, 2018, On the Conditional Entropy of Wireless Networks, 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), Publisher: IEEE

CONFERENCE PAPER

Yang Q, Hassanzadeh P, Gunduz D, Erkip Eet al., 2018, Centralized Caching and Delivery of Correlated Contents over a Gaussian Broadcast Channel, 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), Publisher: IEEE

CONFERENCE PAPER

Mohammadi Amiri M, Gunduz D, 2018, Cache-aided content delivery over erasure broadcast channels, IEEE Transactions on Communications, Vol: 66, Pages: 370-381, ISSN: 0090-6778

A cache-aided broadcast network is studied, in which a server delivers contents to a group of receivers over a packet erasure broadcast channel (BC). The receivers are divided into two sets with regards to their channel qualities: the weak and 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 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 trade-off 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 trade-off.

JOURNAL ARTICLE

Giaconi G, Gunduz D, Poor HV, 2018, Smart Meter Privacy With Renewable Energy and an Energy Storage Device, IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, Vol: 13, Pages: 129-142, ISSN: 1556-6013

JOURNAL ARTICLE

Li Z, Oechtering TJ, Gunduz D, 2018, Privacy against a Hypothesis Testing Adversary, IEEE Transactions on Information Forensics and Security, ISSN: 1556-6013

IEEE 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. Lastly, 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.

JOURNAL ARTICLE

Rosas F, Chen K-C, Gündüz D, 2018, Social learning for resilient data fusion against data falsification attacks., Comput Soc Netw, Vol: 5

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.

JOURNAL ARTICLE

Varasteh M, Rassouli B, Simeone O, Gunduz Det al., 2017, Zero-Delay Source-Channel Coding With a 1-Bit ADC Front End and Correlated Receiver Side Information, IEEE TRANSACTIONS ON COMMUNICATIONS, Vol: 65, Pages: 5429-5444, ISSN: 0090-6778

JOURNAL ARTICLE

Amiri MM, Yang Q, Gunduz D, 2017, Decentralized Caching and Coded Delivery With Distinct Cache Capacities, IEEE TRANSACTIONS ON COMMUNICATIONS, Vol: 65, Pages: 4657-4669, ISSN: 0090-6778

JOURNAL ARTICLE

, 2017, Cache-aided data delivery over erasure broadcast channels, ISSN: 1550-3607

© 2017 IEEE. 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.

CONFERENCE PAPER

, 2017, Audience retention rate aware coded video caching, Pages: 1189-1194

© 2017 IEEE. Users often do not watch an online video content in its entirety, and abort the video before it is completed. This is captured by the notion of audience retention rate, which indicates the portion of a video users watch on average. A decentralized coded caching scheme, called partial coded caching (PCC), is proposed here to take into account both the popularity, and the audience retention rate of the video files in a database. The achievable average delivery rate of PCC is characterised over all possible demand combinations. Two different cache allocation schemes, called the optimal cache allocation (OCA) and the popularity based cache allocation (PCA), are proposed to allocate cache capacities among the different chunks of video files. Numerical results validate that the proposed coded caching scheme, either with the OCA or the PCA, outperforms conventional uncoded caching, as well as the state-of-the-art coded caching schemes that consider only file popularities.

CONFERENCE PAPER

Varasteh M, Rassouli B, Simeone O, Gunduz Det al., 2017, Zero-Delay Source-Channel Coding with a Low-Resolution ADC Front End, IEEE Transactions on Information Theory, Vol: 64, Pages: 1241-1261, ISSN: 0018-9448

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.

JOURNAL ARTICLE

Murin Y, Kaspi Y, Dabora R, Gunduz Det al., 2017, On the Energy-Distortion Tradeoff of Gaussian Broadcast Channels with Feedback, ENTROPY, Vol: 19, ISSN: 1099-4300

JOURNAL ARTICLE

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