Vector Gaussian Multiple Description with Individual and Central Receivers

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. Jointly Gaussian descriptions are optimal in achieving the limiting rates. The key component of the solution is a novel information-theoretic inequality that is used to lower bound the achievable multiple description rates.