Source-Channel Matching for Sources with Memory

Abstract

To be considered for an IEEE Jack Keil Wolf ISIT Student Paper Award. In this paper we analyze the probabilistic matching of sources with memory to channels with memory so that symbol-by-symbol code with memory without anticipation are optimal, with respect to an average distortion and excess distortion probability. We show achievability of such a symbolby-symbol code with memory without anticipation, and we show matching for the Binary Symmetric Markov source (BSMS(p)) over a first-order symmetric channel with a cost constraint.