The Gaussian many-help-one distributed source coding problem

Saurabha Tavildar, Pramod Viswanath, Aaron B. Wagner

Research output: Contribution to journalArticle

Abstract

Jointly Gaussian memoryless sources are observed at Ν distinct terminals. The goal is to efficiently encode the observations in a distributed fashion so as to enable reconstruction of any one of the observations, say the first one, at the decoder subject to a quadratic fidelity criterion. Our main result is a precise characterization of the rate-distortion region when the covariance matrix of the sources satisfies a "tree-structure" condition. In this situation, a natural analog-digital separation scheme optimally trades off the distributed quantization rate tuples and the distortion in the reconstruction: Each encoder consists of a point-to-point Gaussian vector quantizer followed by a Slepian-Wolf binning encoder. We also provide a partial converse that suggests that the tree-structure condition is fundamental.

Original languageEnglish (US)
Article number5361477
Pages (from-to)564-581
Number of pages18
JournalIEEE Transactions on Information Theory
Volume56
Issue number1
DOIs
StatePublished - Jan 1 2010

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coding
reconstruction
Covariance matrix

Keywords

  • Entropy power inequality
  • Gaussian sources
  • Many-help-one problem
  • Network source coding
  • Rate distortion
  • Tree sources

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

Cite this

The Gaussian many-help-one distributed source coding problem. / Tavildar, Saurabha; Viswanath, Pramod; Wagner, Aaron B.

In: IEEE Transactions on Information Theory, Vol. 56, No. 1, 5361477, 01.01.2010, p. 564-581.

Research output: Contribution to journalArticle

Tavildar, Saurabha ; Viswanath, Pramod ; Wagner, Aaron B. / The Gaussian many-help-one distributed source coding problem. In: IEEE Transactions on Information Theory. 2010 ; Vol. 56, No. 1. pp. 564-581.
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