Title: Statistical Mechanical Aspects of Joint Source-channel Coding
Speaker: Ido Kanter, Bar Ilan University, Israel
Date: Thursday, October 23, 2003, 1:30 pm
Location: Hill Center, Room 423, Rutgers University, Busch Campus, Piscataway, NJ
An efficient joint source-channel (S/C) decoder based on the side information of the source and on the MN-Gallager Code over Galois fields, $q$, is presented. The dynamical posterior probabilities are derived either from the statistical mechanical approach for calculation of the entropy for the correlated sequences, or by the Markovian joint S/C algorithm. The Markovian joint S/C decoder has many advantages over the statistical mechanical approach, among them: (a) there is no need for the construction and the diagonalization of a $q \timesq$ matrix and for a solution to saddle point equations in $q$ dimensions; (b) a generalization to a joint S/C coding of an array of two-dimensional bits (or higher dimensions) is achievable; (c) using parametric estimation, an efficient joint S/C decoder with the lack of side information is discussed. Besides the variant joint S/C decoders presented, we also show that the available sets of autocorrelations consist of a convex volume, and its structure can be found using the Simplex algorithm.