Vector Gaussian multiple description with individual and central receivers

Research output: Contribution to journalArticle

Abstract

L multiple descriptions of a vector Gaussian source for individual and central receivers are investigated. The sum rate of the descriptions with covariance distortion measure constraints, in a positive semidefinite ordering, is exactly characterized. For two descriptions, the entire rate region is characterized. The key component of the solution is a novel information-theoretic inequality that is used to lower-bound the achievable multiple description rates. Jointly Gaussian descriptions are optimal in achieving the limiting rates. We also show the robustness of this description scheme: The distortions achieved are no larger when used to describe any non-Gaussian source with the same covariance matrix.

Original languageEnglish (US)
Pages (from-to)2133-2153
Number of pages21
JournalIEEE Transactions on Information Theory
Volume53
Issue number6
DOIs
StatePublished - Jun 1 2007

Keywords

  • Lossy compression
  • Multiple description
  • Quadratic distortion

ASJC Scopus subject areas

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

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