Distributed Source Coding: Theory, Algorithms, and Applications

项目摘要：分布式信源编码(DSC)指的是对两个或多个物理上分离且彼此不通信的信源的输出进行压缩。近年来，在一系列新兴应用(如分布式传感器网络和无线视频)的推动下，DSC重新引起了人们的兴趣。虽然Slepian-Wolf定理给出的理论结果已经有30多年的历史了，但DSC的实用方法直到1999年才出现。为了推动这一领域的发展，本研究涵盖了DSC的理论、算法和应用，重点研究了实际代码设计的难点问题。分布式源代码的基本元素是绑定方案。对于Wyner-Ziv码的设计，PI提出了一种基于Slepian-Wolf编码量化(SWCQ)的设计范式。初步分析结果表明，SWCQ的性能极限反映了经典信源编码的极限。基于TCQ和LDPC码的初始码设计给出了比以前报道的任何结果都好得多的结果。受这些结果的启发，PI建议研究Wyner-Ziv问题的逐次求精，并将SWCQ应用于分层视频编码。该研究还将在同样强大的SWCQ范式下解决更一般的多终端信源编码问题。SWCQ采用非对称Slepian-Wolf编码进行Wyner-Ziv编码，公式终端采用SWCQ进行信源编码，PI将在对每个信源进行量化后探索对称Slepian-Wolf编码。将直接多终端信源编码和间接多终端信源编码(例如，分布式传感器网络中出现的CEO问题)结合起来，将有损DSC视为信源-信道编码问题，并在信道码的基础上结合量化和Slepian-Wolf编码进行代数合并。主要的创新之处在于使用一个单一的SWCQ框架作为代数绑定的体现，以解决不同的代码设计问题和潜在的应用。

Abstract for the project:Distributed source coding (DSC) refers to the compression of the outputsof two or more physically separated sources that do not communicate witheach other. Driven by a host of emerging applications (e.g., distributedsensor networks and wireless video), DSC has assumed renewed interest inrecent years. Although the theoretical result given by the Slepian-Wolftheorem has been known for more than 30 years, practical approaches toDSC did not appear until 1999.Aiming to advance the field, this research covers the theory, algorithms,and applications of DSC, with focus on the hard problem of practical codedesign. The basic element of a distributed source code is the binningscheme. For Wyner-Ziv code design, the PI proposes a paradigm based onSlepian-Wolf coded quantization (SWCQ). Preliminary analytical resultsshow that the performance limits of SWCQ mirror those in classic sourcecoding. Initial code design based on TCQ and LDPC codes gives results thatare significantly better than any previously reported. Inspired by theseresults, the PI proposes to study successive refinement for the Wyner-Zivproblem and apply SWCQ to layered video coding.This research will also tackle the more general problem of multiterminalsource coding under the same powerful paradigm of SWCQ. While asymmetricSlepian-Wolf coding is used in SWCQ for Wyner-Ziv coding, formultiterminal source coding with SWCQ, the PI will explore symmetricSlepian-Wolf coding after quantization of each source. Both directmultiterminal source coding and indirect multiterminal source coding (e.g., the CEO problem that arises in distributed sensor networks) will be treated.The theme of the research is to view lossy DSC as a source-channel codingproblem and perform algebraic binning via the combination of quantizationand Slepian-Wolf coding based on channel codes. The main novelty lies inusing a single SWCQ framework as the embodiment of algebraic binning tosolve different code design problems and address potential applications.