Distributed Source Coding: Theory, Algorithms, and Applications

分布式源编码：理论、算法和应用

• 批准号: 0430720
• 负责人: Zixiang Xiong
• 金额: --
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-08-01 至 2009-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0430720&HistoricalAwards=false
• 关键词: Distributed; Source; Coding; Theory; Algorithms

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.

分布式信源编码（DSC）是指压缩两个或多个物理上分离的信源的输出，这些信源彼此之间不进行通信。在大量新兴应用程序的推动下（例如，分布式传感器网络和无线视频），DSC承担了新的兴趣在最近几年。尽管Slepian-Wolftheorem给出的理论结果已经有30多年的历史了，但直到1999年才出现了DSC的实用方法。为了推动这一领域的发展，本文对DSC的理论、算法和应用进行了研究，重点研究了实际代码设计中的难题。分布式源代码的基本元素是装箱方案。对于Wyner-Ziv码的设计，PI提出了一种基于Slepian-Wolf编码量化（SWCQ）的设计方法。初步的分析结果表明，SWCQ的性能限制反映在经典的源代码。基于TCQ和LDPC码的初始码设计给出的结果明显优于任何以前的报告。受这些结果的启发，PI提出研究Wyner-Ziv问题的连续细化，并将SWCQ应用于分层视频编码，这项研究也将在同样强大的SWCQ范式下解决更普遍的多端信源编码问题。虽然非对称Slepian-Wolf编码在SWCQ中用于Wyner-Ziv编码，但PI将在每个源量化后探索对称Slepian-Wolf编码。直接多端信源编码和间接多端信源编码（例如，本文将有损DSC看作是一个信源信道编码问题，通过量化和基于信道编码的Slepian-Wolf编码相结合的方法进行代数合并。主要的新奇在于使用一个单一的SWCQ框架作为代数装箱的体现，以解决不同的代码设计问题，并解决潜在的应用。