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.

项目摘要：分布式源编码（DSC）是指对两个或多个物理上分离且彼此不通信的源的输出进行压缩。在众多新兴应用（例如分布式传感器网络和无线视频）的推动下，DSC 近年来重新引起人们的兴趣。尽管 Slepian-Wolf 定理给出的理论结果已为人所知 30 多年，但 DSC 的实用方法直到 1999 年才出现。为了推进该领域的发展，本研究涵盖了 DSC 的理论、算法和应用，重点是实际代码设计的难题。分布式源代码的基本元素是分箱方案。对于 Wyner-Ziv 代码设计，PI 提出了一种基于Slepian-Wolf 编码量化（SWCQ）的范例。初步分析结果表明，SWCQ 的性能限制反映了经典源编码中的性能限制。基于 TCQ 和 LDPC 码的初始代码设计给出的结果明显优于之前报道的任何结果。受这些结果的启发，PI 提议研究 Wyner-Ziv 问题的连续细化，并将 SWCQ 应用于分层视频编码。这项研究还将在同样强大的 SWCQ 范式下解决更普遍的多终端源编码问题。虽然 SWCQ 中使用非对称 Slepian-Wolf 编码进行 Wyner-Ziv 编码，但对于使用 SWCQ 的多终端源编码，PI 将在每个源量化后探索对称Slepian-Wolf 编码。直接多终端源编码和间接多终端源编码（例如，分布式传感器网络中出现的CEO问题）都将得到处理。研究的主题是将有损DSC视为源通道编码问题，并通过结合以下方式进行代数分箱：基于信道码的量化和Slepian-Wolf编码。主要新颖之处在于使用单个 SWCQ 框架作为代数分箱的体现来解决不同的代码设计问题并解决潜在的应用。