Publications
374 results found
Mital N, Kralevska K, Ling C, et al., 2019, Storage-repair bandwidth trade-off for wireless caching with partial failure and broadcast repair, IEEE Information Theory Workshop (ITW), Publisher: IEEE, Pages: 41-45
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.
Rassouli B, Gündüz D, 2019, Optimal utility-privacy trade-off with total variation distance as a privacy measure, 2018 IEEE Information Theory Workshop (ITW), Publisher: IEEE
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.
Erdemir E, Gündüz D, Dragotti PL, 2019, Smart meter privacy, Privacy in Dynamical Systems, Pages: 19-41, ISBN: 9789811504921
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.
Erdemir E, Dragotti PL, Gunduz D, 2019, Privacy-Aware Location Sharing with Deep Reinforcement Learning, IEEE International Workshop on Information Forensics and Security (WIFS), Publisher: IEEE, ISSN: 2157-4766
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- Citations: 1
Sun Y, Zhao J, Zhou S, et al., 2019, Heterogeneous Coded Computation across Heterogeneous Workers, IEEE Global Communications Conference (IEEE GLOBECOM), Publisher: IEEE, ISSN: 2334-0983
Hameed MZ, Gyorgy A, Gunduz D, 2019, Communication without Interception: Defense against Modulation Detection, 7th IEEE Global Conference on Signal and Information Processing (IEEE GlobalSIP), Publisher: IEEE, ISSN: 2376-4066
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- Citations: 10
Amiri MM, Duman TM, Gunduz D, 2019, Collaborative Machine Learning at the Wireless Edge with Blind Transmitters, 7th IEEE Global Conference on Signal and Information Processing (IEEE GlobalSIP), Publisher: IEEE, ISSN: 2376-4066
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- Citations: 52
Gindullina E, Badia L, Gunduz D, 2019, Average Age-of-Information with a Backup Information Source, 30th IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Publisher: IEEE, Pages: 445-450, ISSN: 2166-9570
Sreekumar S, Gunduz D, 2019, Hypothesis Testing over a Noisy Channel, IEEE International Symposium on Information Theory (ISIT), Publisher: IEEE, Pages: 2004-2008
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- Citations: 2
Sreekumar S, Gunduz D, 2019, Optimal Privacy-Utility Trade-off under a Rate Constraint, IEEE International Symposium on Information Theory (ISIT), Publisher: IEEE, Pages: 2159-2163
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- Citations: 7
Amiri MM, Gunduz D, 2019, Machine Learning at the Wireless Edge: Distributed Stochastic Gradient Descent Over-the-Air, IEEE International Symposium on Information Theory (ISIT), Publisher: IEEE, Pages: 1432-1436
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- Citations: 59
Amiri MM, Gunduz D, 2019, Over-the-Air Machine Learning at the Wireless Edge, 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Publisher: IEEE, ISSN: 2325-3789
Zhao J, Amiri MM, Gunduz D, 2019, A Low-Complexity Cache-Aided Multi-Antenna Content Delivery Scheme, 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Publisher: IEEE, ISSN: 2325-3789
Somuyiwa SO, Gyorgy A, Gunduz D, 2019, Multicast-Aware Proactive Caching in Wireless Networks with Deep Reinforcement Learning, 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Publisher: IEEE, ISSN: 2325-3789
Triantaris P, Tsimbalo E, Chin WH, et al., 2019, Automatic Modulation Classification in the Presence of Interference, 28th European Conference on Networks and Communications (EuCNC), Publisher: IEEE, Pages: 549-553, ISSN: 2475-6490
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- Citations: 7
Ozfatura E, Gunduz D, Ulukus S, 2019, GRADIENT CODING WITH CLUSTERING AND MULTI-MESSAGE COMMUNICATION, IEEE Data Science Workshop (DSW), Publisher: IEEE, Pages: 42-46
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- Citations: 20
Ozfatura E, Ulukus S, Gunduz D, 2019, DISTRIBUTED GRADIENT DESCENT WITH CODED PARTIAL GRADIENT COMPUTATIONS, 44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, Pages: 3492-3496, ISSN: 1520-6149
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- Citations: 21
Bourtsoulatze E, Kurka DB, Gunduz D, 2019, DEEP JOINT SOURCE-CHANNEL CODING FOR WIRELESS IMAGE TRANSMISSION, 44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, Pages: 4774-4778, ISSN: 1520-6149
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- Citations: 12
Erdemir E, Dragotti PL, Gunduz D, 2019, PRIVACY-COST TRADE-OFF IN A SMART METER SYSTEM WITH A RENEWABLE ENERGY SOURCE AND A RECHARGEABLE BATTERY, 44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, Pages: 2687-2691, ISSN: 1520-6149
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- Citations: 11
Kurka DB, Gunduz D, 2019, Successive Refinement of Images with Deep Joint Source-Channel Coding, Publisher: IEEE
Osia SA, Rassouli B, Haddadi H, et al., 2019, Privacy Against Brute-Force Inference Attacks, Publisher: IEEE
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- Citations: 4
Abad MSH, Ozfatura E, Ercetin O, et al., 2019, Dynamic Content Updates in Heterogeneous Wireless Networks, 15th IEEE/IFIP Wireless On-Demand Network Systems and Services Conference (WONS), Publisher: IEEE, Pages: 107-110
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- Citations: 3
Ceran ET, Gunduz D, Gyorgy A, 2018, A Reinforcement Learning Approach to Age of Information in Multi-User Networks, 29th IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Publisher: IEEE, Pages: 1967-1971
Bourtsoulatze E, Gunduz D, 2018, Cache-Aided Interactive Multiview Video Streaming in Small Cell Wireless Networks, 2018 IEEE 29TH ANNUAL INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS (PIMRC)
Ozfatura E, Rarris T, Gunduz D, et al., 2018, Delay-Aware Coded Caching for Mobile Users, 29th IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Publisher: IEEE
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
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.
Sreekumar S, Gunduz D, Cohen A, 2018, Distributed Hypothesis Testing Under Privacy Constraints, IEEE Information Theory Workshop (ITW), Publisher: IEEE, Pages: 470-474, ISSN: 2475-420X
Faqir O, Nie Y, Kerrigan E, et al., 2018, Energy-efficient communication in mobile aerial relay-assisted networks using predictive control, 6th IFAC Conference on Nonlinear Model Predictive Control, Publisher: Elsevier, Pages: 197-202, ISSN: 2405-8963
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.
Faqir OJ, Kerrigan EC, Gunduz D, 2018, Energy-optimal control in mobile aerial relay-assisted networks, UKACC 12th International Conference on Control (CONTROL), Publisher: IEEE, Pages: 100-100
Faqir OJ, Kerrigan EC, Gunduz D, 2018, Information transmission bounds in mobile communication networks, UKACC 12th International Conference on Control (CONTROL), Publisher: IEEE, Pages: 99-99
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