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IEEE International Workshop on Signal Processing Advances in Wireless Communications

作者： Markus Leinonen Marian Codreanu Markku Juntti Centre for Wireless Communications University of Oulu P.O. Box 4500 90014 Finland

ISBN: (纸本)9781509017508

This paper addresses distributed finite-rate quantized compressed sensing (QCS) acquisition of correlated sparse sources in wireless sensor networks. We propose a distributed variable-rate QCS compression method with complexity-constrained encoding to minimize a weighted sum of the mean square error distortion of the signal reconstruction and the average encoding rate. The variable-rate coding is realized via entropy-constrained vector quantization, whereas the restrained encoding complexity is obtained via vector pre-quantization of CS measurements. We derive necessary optimality conditions for the system blocks for two-sensor case. Numerical results show that our proposed method efficiently exploits the signal correlation, and achieves superior distortion-rate compression performance.

关键词： Compressed sensing distributed source coding Sparse signals Vector quantization Entropy coding

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distributed source coding AUTHENTICATION OF IMAGES WITH CONTRAST AND BRIGHTNESS ADJUSTMENT AND AFFINE WARPING

DISTRIBUTED SOURCE CODING AUTHENTICATION OF IMAGES WITH CONT...

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Picture coding Symposium 2009

作者： Lin, Yao-Chung Varodayan, David Girod, Bernd Stanford Univ Informat Syst Lab Stanford CA 94305 USA

ISBN: (纸本)9781424445936

Media authentication is important in content delivery via untrusted intermediaries, such as peer-to-peer (P2P) file sharing. Many differently encoded versions of a media file might exist. Our previous work applied distributed source coding not only to distinguish the legitimate diversity of encoded images from tampering but also to localize tampered regions in an image already deemed to be inauthentic. In both cases, authentication requires a Slepian-Wolf encoded image projection that is supplied to the decoder. We extend our scheme to authenticate images that have undergone contrast, brightness, and affine warping adjustment. Our approach incorporates an Expectation Maximization algorithm into the Slepian-Wolf decoder. Experimental results demonstrate that the proposed algorithm can distinguish legitimate encodings, of authentic images from illegitimately modified versions. despite arbitrary contrast, brightness, and affine warping adjustment, using authentication data of less than 250 bytes per image.

关键词： Image authentication distributed source coding Expectation Maximization

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distributed source coding TECHNIQUES FOR INTERACTIVE MULTIVIEW VIDEO STREAMING

DISTRIBUTED SOURCE CODING TECHNIQUES FOR INTERACTIVE MULTIVI...

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Picture coding Symposium 2009

作者： Cheung, Ngai-Man Ortega, Antonio Cheung, Gene Univ Southern Calif Los Angeles CA 90089 USA Hewlett Packard Lab Tokyo Japan

ISBN: (纸本)9781424445936

We investigate coding tools for interactive multiview streaming (IMVS), where clients interactively, request desired views for successive video frames, and in response the server sends the appropriate pre-compressed video data to the clients. Solution based on using only I-frames to support view switching would incur high transmission cost, while for that based oil using only P-frames to encode every possible traversal, although it can minimize transmission cost, prohibitive server's storage may be required. Therefore, efficient solutions for IMVS need to consider the trade-off between transmission and storage cost. In this paper, we study the potential use of distributed source coding (DSC) in IMVS. Specifically, we propose two DSC constructions that could achieve good transmission-storage trade-offs. Central to these constructions is a method that can efficiently encode the least significant bits (LSB) of a frame to be decoded. leading to competitive storage and transmission requirements. Experiment results demonstrate these constructions compare favorably to existing tools, and could be valuable for interactive multiview streaming.

关键词： Multiview Video Streaming distributed source coding Slepian-Wolf Wyner-Ziv SP-frames

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distributed source coding AUTHENTICATION OF IMAGES WITH AFFINE WARPING

DISTRIBUTED SOURCE CODING AUTHENTICATION OF IMAGES WITH AFFI...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Lin, Yao-Chung Varodayan, David Girod, Bernd Stanford Univ Informat Syst Lab Stanford CA 94305 USA

ISBN: (纸本)9781424423538

Media authentication is important in content delivery via untrusted intermediaries, such as peer-to-peer (P2P) file sharing. Many differently encoded versions of a media file might exist. Our previous work applied distributed source coding not only to distinguish the legitimate diversity of encoded images from tampering but also to localize tampered regions in an image already deemed to be inauthentic. In both cases, authentication requires a Slepian-Wolf encoded image projection that is supplied to the decoder. We extend our scheme to authenticate images that have undergone affine warping. Our approach incorporates an Expectation Maximization algorithm into the Slepian-Wolf decoder. Experimental results demonstrate that the proposed algorithm can distinguish legitimate encodings of authentic images from illegitimately modified versions, despite an arbitrary affine warping, using authentication. data of less than 250 bytes per image.

关键词： Image authentication distributed source coding Expectation Maximization

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distributed and Cascade Lossy source coding With a Side Information "Vending Machine"

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IEEE TRANSACTIONS ON INFORMATION THEORY 2013年第10期59卷 6807-6819页

作者： Ahmadi, Behzad Simeone, Osvaldo New Jersey Inst Technol Dept Elect & Comp Engn Newark NJ 07102 USA New Jersey Inst Technol CWCSPR Newark NJ 07102 USA

source coding with a side information "vending machine" is a recently proposed framework in which the statistical relationship between the side information and the source, instead of being given and fixed as in the classical Wyner-Ziv problem, can be controlled by the decoder. This control action is selected by the decoder based on the message encoded by the source node. Unlike conventional settings, the message can thus carry not only information about the source to be reproduced at the decoder, but also control information aimed at improving the quality of the side information. In this paper, the analysis of the tradeoffs between rate, distortion, and cost associated with the control actions is extended from the previously studied point-to-point setup to two basic multiterminal models. First, a distributed source coding model is studied, in which two encoders communicate over rate-limited links to a decoder, whose side information can be controlled. The control actions are selected by the decoder based on the messages encoded by both source nodes. For this setup, inner bounds are derived on the rate-distortion-cost region for both cases in which the side information is available causally and noncausally at the decoder. These bounds are shown to be tight under specific assumptions, including the scenario in which the sequence observed by one of the nodes is a function of the source observed by the other and the side information is available causally at the decoder. Then, a cascade scenario in which three nodes are connected in a cascade and the last node has controllable side information is also investigated. For this model, the rate-distortion-cost region is derived for general distortion requirements and under the assumption of causal availability of side information at the last node.

关键词： Cascade source coding distributed source coding observation costs rate-distortion theory side information side information vending machine

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Rate and Power Allocation Under the Pairwise distributed source coding Constraint

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IEEE TRANSACTIONS ON COMMUNICATIONS 2009年第12期57卷 3771-3781页

作者： Li, Shizheng Ramamoorthy, Aditya Iowa State Univ Dept Elect & Comp Engn Ames IA 50011 USA

We consider the problem of rate and power allocation for a sensor network under the pairwise distributed source coding constraint. For noiseless source-terminal channels, we show that the minimum sum rate assignment can be found by finding a minimum weight arborescence in an appropriately defined directed graph. For orthogonal noisy source-terminal channels, the minimum sum power allocation can be found by finding a minimum weight matching forest in a mixed graph. Numerical results are presented for both cases showing that our solutions always outperform previously proposed solutions. The gains are considerable when source correlations are high.

关键词： distributed source coding Slepian-Wolf theorem matching forest directed spanning tree resource allocation

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Lossy distributed source coding Using Graphs

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IEEE COMMUNICATIONS LETTERS 2009年第4期13卷 262-264页

作者： Choi, Suhan Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA

In the letter, lossy distributed source coding using graphs is considered. This corresponds to the source coding part of the graph-based frame [1] for transmission of analog correlated sources over the multiple-access channel (MAC). Consequently, it is shown that a pair of analog correlated sources can be reliably represented into a bipartite graph by allowing certain amount of distortion. An achievable rate-distortion region for this problem is also provided. Therefore, it can be concluded that, for transmission of any (both discrete and continuous) set of correlated sources over MACs, graphs can be used as discrete interface between source coding and the channel coding modules.

关键词： distributed source coding correlated messages random graphs multiple-access channels

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Lattices for distributed source coding: Jointly Gaussian sources and Reconstruction of a Linear Function

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IEEE TRANSACTIONS ON INFORMATION THEORY 2009年第12期55卷 5628-5651页

作者： Krithivasan, Dinesh Pradhan, S. Sandeep Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA

Consider a pair of correlated Gaussian sources (X-1, X-2). Two separate encoders observe the two components and communicate compressed versions of their observations to a common decoder. The decoder is interested in reconstructing a linear combination of X-1 and X-2 to within a mean-square distortion of D. We obtain an inner bound to the optimal rate-distortion region for this problem. A portion of this inner bound is achieved by a scheme that reconstructs the linear function directly rather than reconstructing the individual components X-1 and X-2 first. This results in a better rate region for certain parameter values. Our coding scheme relies on lattice coding techniques in contrast to more prevalent random coding arguments used to demonstrate achievable rate regions in information theory. We then consider the case of linear reconstruction of K sources and provide an inner bound to the optimal rate-distortion region. Some parts of the inner bound are achieved using the following coding structure: lattice vector quantization followed by "correlated" lattice-structured binning.

关键词： Berger-Tung inner bound distributed source coding function reconstruction lattice codes structured coding

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Lossy distributed source coding Using LDPC Codes

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IEEE COMMUNICATIONS LETTERS 2009年第2期13卷 136-138页

作者： Sartipi, Mina Fekri, Faramarz Univ Tennessee Chattanooga Dept Comp Sci & Engn Chattanooga TN 37403 USA Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA

In this paper, we propose a practical scheme for lossy distributed source coding with side information available at the decoder. Our proposed scheme is based on sending parity bits using LDPC codes. We provide the design procedure for the LDPC code that guarantees performance close to the Wyner-Ziv limit for long LDPC codes. Using simulation results, we show that the proposed method performs close to the theoretical limit for even short length codes.

关键词： Wyner-Ziv limit distributed source coding LDPC codes non-uniform code

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Dynamic Compression-Transmission for Energy-Harvesting Multihop Networks With Correlated sources

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IEEE-ACM TRANSACTIONS ON NETWORKING 2014年第6期22卷 1729-1741页

作者： Tapparello, Cristiano Simeone, Osvaldo Rossi, Michele Univ Padua Dept Informat Engn I-35131 Padua Italy NJIT CWCSPR Newark NJ 07102 USA

Energy-harvesting wireless sensor networking is an emerging technology with applications to various fields such as environmental and structural health monitoring. A distinguishing feature of wireless sensors is the need to perform both source coding tasks, such as measurement and compression, and transmission tasks. It is known that the overall energy consumption for source coding is generally comparable to that of transmission, and that a joint design of the two classes of tasks can lead to relevant performance gains. Moreover, the efficiency of source coding in a sensor network can be potentially improved via distributed techniques by leveraging the fact that signals measured by different nodes are correlated. In this paper, a data-gathering protocol for multihop wireless sensor networks with energy-harvesting capabilities is studied whereby the sources measured by the sensors are correlated. Both the energy consumptions of source coding and transmission are modeled, and distributed source coding is assumed. The problem of dynamically and jointly optimizing the source coding and transmission strategies is formulated for time-varying channels and sources. The problem consists in the minimization of a cost function of the distortions in the source reconstructions at the sink under queue stability constraints. By adopting perturbation-based Lyapunov techniques, a close-to-optimal online scheme is proposed that has an explicit and controllable tradeoff between optimality gap and queue sizes. The role of side information available at the sink is also discussed under the assumption that acquiring the side information entails an energy cost.

关键词： Data gathering distributed source coding energy harvesting Lyapunov optimization wireless sensor networks

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