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The Three-terminal Interactive Lossy source coding Problem

IEEE TRANSACTIONS ON INFORMATION THEORY 2017年第1期63卷 532-562页

作者： Rey Vega, Leonardo Piantanida, Pablo Hero, Alfred O., III Univ Buenos Aires Dept Elect CONICET Ctr Simulacion Computac Buenos Aires DF Argentina Univ Paris Sud CNRS Lab Signaux & Syst Cent Supelec F-91192 Gif Sur Yvette France Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA

In this paper, we explore the three-node multi-terminal lossy source coding problem, which seems to offer a formidable mathematical complexity. We derive an inner bound to the general rate-distortion region of this problem, which is a natural extension of the seminal work by Kaspi on the interactive two-terminal source coding problem. It is shown that this (rather involved) inner bound contains several rate-distortion regions of some relevant source coding settings. In this way, besides the non-trivial extension of the interactive two terminal problem, our results can be seen as a generalization and hence unification of several previous works in the field. By specializing the inner bound to particular cases, we obtain some novel rate-distortion regions for several multi-terminal lossy source coding problems.

关键词： multi-terminal source coding Wyner-Ziv rate-distortion region Berger-Tung inner bound interactive lossy source coding distributed lossy source coding

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Communication Versus Computation: Duality for multiple-Access Channels and source coding

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IEEE TRANSACTIONS ON INFORMATION THEORY 2019年第1期65卷 292-301页

作者： Zhu, Jingge Lim, Sung Hoon Gastpar, Michael Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94720 USA Korean Inst Ocean Sci & Technol ICT Convergence Unit Busan 49111 South Korea Ecole Polytech Fed Sch Comp & Commun Sci CH-1015 Lausanne Switzerland

Computation codes in network information theory are designed for scenarios where the decoder is not interested in recovering the information sources themselves, but only a function thereof. Korner and Marton showed for distributed source coding (DSC) that such function decoding can be achieved more efficiently than decoding the full information sources. Compute-forward has shown that function decoding, in combination with network coding ideas, is a useful building block for end-to-end communication over a network. In both cases, good computation codes are the key component in the coding schemes. Could these same codes simultaneously also enable full message decoding over a sufficiently strong multiple-access channel (MAC)? This work establishes a partial negative answer and converse result. Specifically, for any code that is known to be a good computation code for some MAC, we characterize a class of MACs for which that code cannot enable full message decoding (and vice versa). Finally, an analogous duality result is established for a related DSC problem.

关键词： Function computation code duality multiple access channel compute-forward multi-terminal source coding structured code

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source coding With a Listening-Helper

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IEEE TRANSACTIONS ON INFORMATION THEORY 2023年第4期69卷 2135-2151页

作者： Bross, Shraga I. Bar Ilan Univ Fac Engn Ramat Gan Israel

We consider the cooperative coding of a pair of correlated memoryless source and side-information sequences wherein an encoder assisted by a side-information aided listening-helper describe the source and side-information to a receiver. We obtain a single-letter characterization of the rate region in both cases: when the decoder reconstructs just the source and when it reconstructs both the source and side-information. In the quadratic Gaussian setting we determine the optimal law characterizing the rate region using a technique introduced by Courtade in combination with a conditional version of the converse for the Gaussian CEO problem.

关键词： Decoding Distortion Markov processes source coding Random variables Distortion measurement Indexes multi-terminal source coding non-causal helper non-causal side-information cooperation

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A Truncated Prediction Framework for Streaming Over Erasure Channels

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IEEE TRANSACTIONS ON INFORMATION THEORY 2017年第11期63卷 7322-7351页

作者： Etezadi, Farrokh Khisti, Ashish Chen, Jun Univ Toronto Toronto ON M5S 3G4 Canada Univ Toronto Elect & Comp Engn Dept Toronto ON M5S 3G4 Canada Samsung Elect Modem R&D San Diego CA 92122 USA McMaster Univ Hamilton ON L8S 4K1 Canada

We propose a new coding technique for sequential transmission of a stream of Gauss-Markov sources over erasure channels under a zero decoding delay constraint. Our proposed scheme is a combination (hybrid) of predictive coding with truncated memory, and quantization-and-binning. We study the optimality of our proposed scheme using an information theoretic model. In our setup, the encoder observes a stream of source vectors that are spatially independent and identically distributed (i.i.d.) and temporally sampled from a first-order stationary Gauss-Markov process. The channel introduces an erasure burst of a certain maximum length B, starting at an arbitrary time, not known to the transmitter. The reconstruction of each source vector at the destination must be with zero delay and satisfy a quadratic distortion constraint with an average distortion of D. The decoder is not required to reconstruct those source vectors that belong to the period spanning the erasure burst and a recovery window of length W following it. We study the minimum compression rate R(B, W, D) in this setup. As our main result, we establish upper and lower hounds on the compression rate. The upper bound (achievability) is based on our hybrid scheme. It achieves significant gains over baseline schemes such as (leaky) predictive coding, memoryless binning, a separation-based scheme, and a group of pictures based scheme. The lower hound is established by observing connection to a network source coding problem. The bounds simplify in the high resolution regime, where we provide explicit expressions whenever possible, and identify conditions when the proposed scheme is close to optimal. We finally discuss the interplay between the parameters of our burst erasure channel and the statistical channel models and explain how the hounds in the former model can be used to derive insights into the simulation results involving the latter. In particular, our proposed scheme outperforms the baseline schemes over

关键词： Rate distortion theory sequential source coding burst erasure channels multi-terminal source coding joint source-channel coding

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Joint source-decoding in large scale sensor networks using Markov random field models

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SIGNAL PROCESSING 2010年第12期90卷 3134-3146页

作者： Yahampath, Pradeepa Univ Manitoba Dept Elect & Comp Engn Winnipeg MB R3T 5V6 Canada

An approach to scalable joint source decoding in large-scale sensor networks, based on Markov-random filed (MRF) modeling of the spatio-temporal correlation in the observations is presented. This approach exploits the correlation among a multitude of sensors for joint decoding at a central decoder, while using simple distributed quantizers in individual sensors. The decoder derivations are provided for Slepian-Wolf coded quantization based on both sample-by-sample (scalar) binning and vector binning schemes constructed via channel code partitioning. Simulation results are presented to demonstrate the performance achievable with the proposed decoding approach. (C) 2010 Elsevier B.V. All rights reserved.

关键词： Distributed quantization Slepian-Wolf coding multi-terminal source coding Markov-random field models

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Optimal Delay-Reconstruction Tradeoffs in Peer-to-Peer Networks

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2011年第5期29卷 1055-1063页

作者： Ahmed, Ebad Wagner, Aaron B. Cornell Univ Sch Elect & Comp Engn Ithaca NY 14853 USA

We study the tradeoff between delay and partial reconstruction in peer-to-peer networks, i.e., the number of messages a peer must obtain to reconstruct a given fraction of the file. We present a coding scheme based on erasure compression and Slepian-Wolf binning, in which peers generate coded messages based on their current knowledge of the file. Assuming symmetric peers, we show that the coding scheme provides a Pareto optimal tradeoff between delay and reconstruction, which we characterize. In the process of proving the result, we establish an improved outer bound on the rate region of the general multi-terminal source coding problem. We further show that in the case of asymmetric peers, the coding scheme is not optimal.

关键词： Peer to peer computing erasure data compression decentralized encoding delay-reconstruction tradeoff multi-terminal source coding

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Collaborative Information Bottleneck

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IEEE TRANSACTIONS ON INFORMATION THEORY 2019年第2期65卷 787-815页

作者： Vera, Matias Vega, Leonardo Rey Piantanida, Pablo Univ Buenos Aires Fac Ingn C1063ACV Buenos Aires DF Argentina CSC CONICET C1425FQD Buenos Aires DF Argentina Univ Paris Sud Cent Supelec French Natl Ctr Sci Res F-91190 Gif Sur Yvette France Univ Montreal Montreal Inst Learning Algorithms Montreal PQ H3T 1N8 Canada

This paper investigates a multi-terminal source coding problem under a logarithmic loss fidelity which does not necessarily lead to an additive distortion measure. The problem is motivated by an extension of the information bottleneck method to a multi-source scenario where several encoders have to build cooperatively rate-limited descriptions of their sources in order to maximize information with respect to other unobserved (hidden) sources. More precisely, we study fundamental information-theoretic limits of the so-called: 1) two-way collaborative information bottleneck (TW-CIB) and 2) the collaborative distributed information bottleneck (CDIB) problems. The TW-CIB problem consists of two distant encoders that separately observe marginal (dependent) components X-1 and X-2 and can cooperate through multiple exchanges of limited information with the aim of extracting information about hidden variables (Y-1, Y-2), which can be arbitrarily dependent on (X-1, X-2). On the other hand, in CDIB, there are two cooperating encoders which separately observe X-1 and X-2 and a third node which can listen to the exchanges between the two encoders in order to obtain information about a hidden variable Y. The relevance (figure-of-merit) is measured in terms of a normalized (per-sample) multi-letter mutual information metric (log-loss fidelity), and an interesting tradeoff arises by constraining the complexity of descriptions, measured in terms of the rates needed for the exchanges between the encoders and decoders involved. Inner and outer bounds to the complexity-relevance region of these problems are derived from which optimality is characterized for several cases of interest. Our resulting theoretical complexity-relevance regions are finally evaluated for binary symmetric and Gaussian statistical models, showing theoretical tradeoffs between the complexity-constrained descriptions and their relevance with respect to the hidden variables.

关键词： multi-terminal source coding logarithmic loss distributed source coding noisy rate-distortion side information interactive lossy source coding information bottleneck Shannon theory

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Information-Theoretic Caching: Sequential coding for Computing

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IEEE TRANSACTIONS ON INFORMATION THEORY 2016年第11期62卷 6393-6406页

作者： Wang, Chien-Yi Lim, Sung Hoon Gastpar, Michael Univ Paris Saclay Telecom ParisTech Commun & Elect Dept F-75013 Paris France Ecole Polytech Fed Lausanne Sch Comp & Commun Sci CH-1015 Lausanne Switzerland

Under the paradigm of caching, partial data are delivered before the actual requests of users are known. In this paper, this problem is modeled as a canonical distributed source coding problem with side information, where the side information represents the users' requests. For the single-user case, a single-letter characterization of the optimal rate region is established, and for several important special cases, closed-form solutions are given, including the scenario of uniformly distributed user requests. In this case, it is shown that the optimal caching strategy is closely related to total correlation and Wyner's common information. Using the insight gained from the single-user case, three two-user scenarios admitting single-letter characterization are considered, which draw connections to existing source coding problems in the literature: the Gray-Wyner system and distributed successive refinement. Finally, the model studied by Maddah-Ali and Niesen is rephrased to make a comparison with the considered information-theoretic model. Although the two caching models have a similar behavior for the single-user case, it is shown through a two-user example that the two caching models behave differently in general.

关键词： Coded caching function computation Gray-Wyner system information bottleneck multi-terminal source coding source coding with side information successive refinement

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Universal Quantization for Separate Encodings and Joint Decoding of Correlated sources

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IEEE TRANSACTIONS ON INFORMATION THEORY 2015年第12期61卷 6465-6474页

作者： Reani, Avraham Merhav, Neri Technion Israel Inst Technol Dept Elect Engn IL-32000 Haifa Israel

We consider the multi-user lossy source-coding problem for continuous alphabet sources. In a previous work, Ziv proposed a single-user universal coding scheme which uses uniform quantization with dither, followed by a lossless source encoder (entropy coder). In this paper, we generalize Ziv's scheme to the multi-user setting. For this generalized universal scheme, upper bounds are derived on the redundancies, defined as the differences between the actual rates and the closest corresponding rates on the boundary of the rate region. For the mean-square error distortion measure, it is shown that this scheme can achieve redundancies of no more than 0.754 b per sample for each user. These bounds are obtained without the knowledge of the multi-user rate region, which is an open problem in general. As a direct consequence of these results, the inner and outer bounds on the rate-distortion achievable region are obtained.

关键词： multi-terminal source coding dithered quantization universal source coding scalar quantization Slepian-Wolf coding

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Low-Delay Joint source-Channel Mappings for the Gaussian MAC

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IEEE COMMUNICATIONS LETTERS 2014年第2期18卷 249-252页

作者： Kron, Johannes Alajaji, Fady Skoglund, Mikael Royal Inst Technol KTH Sch Elect Engn Stockholm Sweden Queens Univ Dept Math & Stat Kingston ON K7L 3N6 Canada

The bivariate Gaussian multiterminal source coding problem with transmission over the Gaussian multiple-access channel is studied. We propose the use of low-delay joint source-channel mappings and show how performance saturation, which is unavoidable with linear transmission, can be overcome by optimizing the mappings. The optimized mappings are in general nonlinear and perform a combination of hard and soft decision signaling for the error-resilient transmission of analog data.

关键词： Joint source-channel coding low-delay transmission multi-terminal source coding Gaussian multiple-access channel correlated sources mean square error

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