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IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY 2021年 2卷 1267-1278页

作者： Steiner, Steffen Kuehn, Volker Stark, Maximilian Bauch, Gerhard Univ Rostock Inst Commun Engn D-18119 Rostock Germany Hamburg Univ Technol Inst Commun D-21073 Hamburg Germany

This paper addresses the optimization of distributed compression in a sensor network. A direct communication among the sensors is not possible so that noisy measurements of a single relevant signal have to be locally compressed in order to meet the rate constraints of the communication links to a common receiver. This scenario is widely known as the Chief Executive Officer (CEO) problem and represents a long-standing problem in information theory. In recent years significant progress has been achieved and the rate region has been completely characterized for specific distributions of involved processes and distortion measures. While algorithmic solutions of the CEO problem are principally known, their practical implementation quickly becomes challenging due to complexity reasons. In this contribution, an efficient greedy algorithm to determine feasible solutions of the CEO problem is derived using the information bottleneck (IB) approach. Following the Wyner-Ziv coding principle, the quantizers are successively designed using already optimized quantizer mappings as side-information. However, processing this side-information in the optimization algorithm becomes a major bottleneck because the memory complexity grows exponentially with number of sensors. Therefore, a sequential compression scheme leading to a compact representation of the side-information and ensuring moderate memory requirements even for larger networks is introduced. This internal compression is optimized again by means of the IB method. Numerical results demonstrate that the overall loss in terms of relevant mutual information can be made sufficiently small even with a significant compression of the side-information. The performance is compared to separately optimized quantizers and a centralized quantization. Moreover, the influence of the optimization order for asymmetric scenarios is discussed.

关键词： Distortion measurement Distortion Optimization Loss measurement Noise measurement source coding Receivers Chief executive officer distributed compression distributed source coding information bottleneck

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distributed source coding of Correlated Gaussian Remote sources

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IEEE TRANSACTIONS ON INFORMATION THEORY 2012年第8期58卷 5059-5085页

作者： Oohama, Yasutada Univ Electrocommun Dept Commun Engn & Informat Tokyo 1828585 Japan

We consider the distributed source coding system for correlated memoryless Gaussian remote sources specified with correlated Gaussian random variables X-i, i = 1, 2, ..., L. We deal with the case where each of distributed encoders cannot directly observe the source X-i but its noisy version Y-i = X-i + N-i. Here, N-i, i = 1, 2, ..., L are independent additive Gaussian noises also independent of X-i, i = 1, 2, ..., L. On this coding system, the determination problem of the rate distortion region remains open in general. In this paper, we derive explicit outer and inner bounds of the rate distortion region. We further find an explicit sufficient condition for those two bounds to match. We also study the sum rate part of the rate distortion region when the correlation has some symmetrical property. We derive an explicit upper bound of the sum rate part from the inner bounds of the rate distortion region. On a lower bound, we derive a new explicit bound by making full use of the symmetrical property of the correlation. We further derive an explicit necessary and sufficient condition for the lower bound to coincide with the upper bound.

关键词： distributed source coding Gaussian remote sources inner and outer bounds matching condition rate-distortion region

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distributed source coding using chaos-based cryptosystem

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COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION 2012年第12期17卷 5110-5116页

作者： Zhou, Junwei Wong, Kwok-Wo Chen, Jianyong City Univ Hong Kong Dept Elect Engn Hong Kong Hong Kong Peoples R China Shenzhen Univ Dept Comp Applicat Technol Shenzhen 518060 Peoples R China

A distributed source coding scheme is proposed by incorporating a chaos-based cryptosystem in the Slepian-Wolf coding. The punctured codeword generated by the chaos-based cryptosystem results in ambiguity at the decoder side. This ambiguity can be removed by the maximum a posteriori decoding with the help of side information. In this way, encryption and source coding are performed simultaneously. This leads to a simple encoder structure with low implementation complexity. Simulation results show that the encoder complexity is lower than that of existing distributed source coding schemes. Moreover, at small block size, the proposed scheme has a performance comparable to existing distributed source coding schemes. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Chaos Encryption distributed source coding Slepian-Wolf coding

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Hypergraph-Based source Codes for Function Computation Under Maximal Distortion

IEEE JOURNAL ON SELECTED AREAS IN INFORMATION THEORY

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IEEE JOURNAL ON SELECTED AREAS IN INFORMATION THEORY 2022年第4期3卷 824-838页

作者： Basu, Sourya Seo, Daewon Varshney, Lav R. Univ Illinois Coordinated Sci Lab Urbana IL 61801 USA Univ Illinois Dept Elect & Comp Engn Urbana IL 61801 USA Daegu Gyeongbuk Inst Sci & Technol Dept Elect Engn & Comp Sci Daegu 42988 South Korea

This work investigates functional source coding problems with maximal distortion, motivated by approximate function computation in many modern applications. The maximal distortion treats imprecise reconstruction of a function value as good as perfect computation if it deviates less than a tolerance level, while treating reconstruction that differs by more than that level as a failure. Using a geometric understanding of the maximal distortion, we propose a hypergraph-based source coding scheme for function computation that is constructive in the sense that it gives an explicit procedure for finding optimal or good auxiliary random variables. Moreover, we find that the hypergraph-based coding scheme achieves the optimal rate-distortion function in the setting of coding for computing with side information and achieves the Berger-Tung sum-rate inner bound in the setting of distributed source coding for computing. It also achieves the El Gamal-Cover inner bound for multiple description coding for computing and is optimal for successive refinement and cascade multiple description problems for computing. Lastly, the benefit of complexity reduction of finding a forward test channel is shown for a class of Markov sources.

关键词： coding for computing functional compression distributed source coding hypergraph

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distributed coding of Quantized Random Projections

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2020年 68卷 5924-5939页

作者： Goukhshtein, Maxim Boufounos, Petros T. Koike-Akino, Toshiaki Draper, Stark C. Univ Toronto Dept Elect & Comp Engn Toronto ON Canada Mitsubishi Elect Res Labs MERL Cambridge MA 02139 USA

In this paper we propose a new framework for distributed source coding of structured sources, such as sparse signals. Our framework capitalizes on recent advances in the theory of linear inverse problems and signal representations using incoherent projections. Our approach acquires and quantizes incoherent linear measurements of the signal, which are represented as separate bitplanes. Each bitplane is coded using a distributed source code of the appropriate rate, and transmitted. The decoder, starts from the least significant biplane and, using a prediction of the signal as side information, iteratively recovers each bitplane based on the source prediction and the signal, assuming all the previous bitplanes of lower significance have already been recovered. We provide theoretical results guiding the rate selection, relying only on the least squares prediction error of the source. This is in contrast to existing approaches which rely on difficult-to-estimate information-theoretic metrics to set the rate. We validate our approach using simulations on remote-sensing multispectral images, comparing them with existing approaches of similar complexity.

关键词： distributed source coding lossy compression quantization sparsity compressed sensing syndrome decoding low complexity encoder side information

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Minimal Information Exchange for Secure Image Hash-Based Geometric Transformations Estimation

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IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2020年 15卷 3482-3496页

作者： Guerrini, Fabrizio Dalai, Marco Leonardi, Riccardo Univ Brescia CNIT Dept Informat Engn I-25123 Brescia Italy

Signal processing applications dealing with secure transmission are enjoying increasing attention lately. This paper provides some theoretical insights as well as a practical solution for transmitting a hash of an image to a central server to be compared with a reference image. The proposed solution employs a rigid image registration technique viewed in a distributed source coding perspective. In essence, it embodies a phase encoding framework to let the decoder estimate the transformation parameters using a very modest amount of information about the original image. The problem is first cast in an ideal setting and then it is solved in a realistic scenario, giving more prominence to low computational complexity in both the transmitter and receiver, minimal hash size, and hash security. Satisfactory experimental results are reported on a standard images set.

关键词： Image registration Cryptography Bandwidth Forensics Information security source coding Phase spectrum secure communication Fourier-Mellin transform rigid image registration distributed source coding image hashing

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Vector Gaussian CEO Problem Under Logarithmic Loss and Applications

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IEEE TRANSACTIONS ON INFORMATION THEORY 2020年第7期66卷 4183-4202页

作者： Ugur, Yigit Aguerri, Inaki Estella Zaidi, Abdellatif Univ Paris Est Lab Informat Gaspard Monge F-77454 Champs Sur Marne France Huawei Technol Paris Res Ctr Math & Algorithm Sci Lab F-92100 Boulogne France Telephon Innovac Alpha Barcelona 08019 Spain

In this paper, we study the vector Gaussian Chief Executive Officer (CEO) problem under logarithmic loss distortion measure. Specifically, K >= 2 agents observe independently corrupted Gaussian noisy versions of a remote vector Gaussian source, and communicate independently with a decoder or CEO over rate-constrained noise-free links. The CEO also has its own Gaussian noisy observation of the source and wants to reconstruct the remote source to within some prescribed distortion level where the incurred distortion is measured under the logarithmic loss penalty criterion. We find an explicit characterization of the rate-distortion region of this model. The result can be seen as the counterpart to the vector Gaussian setting of that by Courtade-Weissman which provides the rate-distortion region of the model in the discrete memoryless setting. For the proof of this result, we obtain an outer bound by means of a technique that relies on the de Bruijn identity and the properties of Fisher information. The approach is similar to Ekrem-Ulukus outer bounding technique for the vector Gaussian CEO problem under quadratic distortion measure, for which it was there found generally non-tight;but it is shown here to yield a complete characterization of the region for the case of logarithmic loss measure. Also, we show that Gaussian test channels with time-sharing exhaust the Berger-Tung inner bound, which is optimal. Furthermore, application of our results allows us to find the complete solutions of two related problems: a quadratic vector Gaussian CEO problem with determinant constraint and the vector Gaussian distributed Information Bottleneck problem. Finally, we develop Blahut-Arimoto type algorithms that allow to compute numerically the regions provided in this paper, for both discrete and Gaussian models. With the known relevance of the logarithmic loss fidelity measure in the context of learning and prediction, the proposed algorithms may find usefulness in a variety of app

关键词： Loss measurement Distortion Rate-distortion Distortion measurement source coding Noise measurement Decoding Multiterminal source coding distributed source coding CEO problem rate-distortion region Berger-Tung inner bound logarithmic loss information bottleneck Blahut-Arimoto algorithm

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Codebook Cardinality Spectrum of distributed Arithmetic coding for Independent and Identically-distributed Binary sources

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IEEE TRANSACTIONS ON INFORMATION THEORY 2020年第10期66卷 6580-6596页

作者： Fang, Yong Stankovic, Vladimir Changan Univ Sch Informat Engn Xian 710064 Peoples R China Univ Strathclyde Dept Elect & Elect Engn Glasgow G1 1XW Lanark Scotland

It was demonstrated that, as a nonlinear implementation of Slepian-Wolf coding, distributed Arithmetic coding (DAC) outperforms traditional Low-Density Parity-Check (LPDC) codes for short code length and biased sources. This fact triggers research efforts into theoretical analysis of DAC. In our previous work, we proposed two analytical tools, Codebook Cardinality Spectrum (CCS) and Hamming Distance Spectrum, to analyze DAC for independent and identically-distributed (i.i.d.) binary sources with uniform distribution. This article extends our work on CCS from uniform i.i.d. binary sources to biased i.i.d. binary sources. We begin with the final CCS and then deduce each level of CCS backwards by recursion. The main finding of this article is that the final CCS of biased i.i.d. binary sources is not uniformly distributed over [0, 1). This article derives the final CCS of biased i.i.d. binary sources and proposes a numerical algorithm for calculating CCS effectively in practice. All theoretical analyses are well verified by experimental results.

关键词： Decoding Parity check codes Channel coding Correlation Complexity theory Estimation distributed source coding Slepian-Wolf coding distributed arithmetic coding codebook cardinality spectrum biased sources

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An Index coding Approach to Caching With Uncoded Cache Placement

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IEEE TRANSACTIONS ON INFORMATION THEORY 2020年第3期66卷 1318-1332页

作者： Wan, Kai Tuninetti, Daniela Piantanida, Pablo Univ Paris Sud Cent Supelec French Natl Ctr Sci Res CNRS L2S F-91192 Gif Sur Yvette France Tech Univ Berlin Elect Engn & Comp Sci Dept D-10587 Berlin Germany Univ Illinois Dept Elect & Comp Engn Chicago IL 60607 USA Univ Paris Sud French Natl Ctr Sci Res CNRS F-91192 Gif Sur Yvette France Univ Montreal MILA Montreal PQ H3T 1N8 Canada

Caching is an efficient way to reduce network traffic congestion during peak hours, by storing some content at the user's local cache memory, even without knowledge of user's later demands. Maddah-Ali and Niesen proposed a two-phase (placement phase and delivery phase) coded caching strategy for broadcast channels with cache-aided users. This paper investigates the same model under the constraint that content is placed uncoded within the caches, that is, when bits of the files are simply copied within the caches. When the cache contents are uncoded and the users' demands are revealed, the caching problem can be connected to an index coding problem. This paper focuses on deriving fundamental performance limits for the caching problem by using tools for the index coding problem that were either known or are newly developed in this work. First, a converse bound for the caching problem under the constraint of uncoded cache placement is proposed based on the "acyclic index coding converse bound." This converse bound is proved to be achievable by the Maddah-Ali and Niesen's scheme when the number of files is not less than the number of users, and by a newly derived index coding achievable scheme otherwise. The proposed index coding achievable scheme is based on distributed source coding and strictly improves on the widely used "composite (index) coding" achievable bound and its improvements, and is of independent interest. An important consequence of the findings of this paper is that advancements on the coded caching problem posed by Maddah-Ali and Niesen are thus only possible by considering strategies with coded placement phase. A recent work by Yu et al has however shown that coded cache placement can at most half the network load compared to the results presented in this paper.

关键词： Coded caching uncoded cache placement index coding distributed source coding

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Energy-efficient data transmission technique for wireless sensor networks based on DSC and virtual MIMO

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ETRI JOURNAL 2020年第3期42卷 341-350页

作者： Singh, Manish Kumar Amin, Syed Intekhab KIET Grp Inst Ghaziabad India Jamia Millia Islamia New Delhi India

In a wireless sensor network (WSN), the data transmission technique based on the cooperative multiple-input multiple-output (CMIMO) scheme reduces the energy consumption of sensor nodes quite effectively by utilizing the space-time block coding scheme. However, in networks with high node density, the scheme is ineffective due to the high degree of correlated data. Therefore, to enhance the energy efficiency in high node density WSNs, we implemented the distributed source coding (DSC) with the virtual multiple-input multiple-output (MIMO) data transmission technique in the WSNs. The DSC-MIMO first compresses redundant source data using the DSC and then sends it to a virtual MIMO link. The results reveal that, in the DSC-MIMO scheme, energy consumption is lower than that in the CMIMO technique;it is also lower in the DSC single-input single-output (SISO) scheme, compared to that in the SISO technique at various code rates, compression rates, and training overhead factors. The results also indicate that the energy consumption per bit is directly proportional to the velocity and training overhead factor in all the energy saving schemes.

关键词： cluster head CMIMO distributed source coding DSC-MIMO sensor nodes wireless sensor network

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