Asymmetric Slepian-Wolf Coding of Nonstationarily-Correlated M-ary Sources with Sliding-Window Belief Propagation

Abstract

Asymmetric Slepian-Wolf coding (ASWC) of M-ary sources with nonstationary correlation is a very useful model for many practical problems. An effective implementation of this coding scheme is to binarize each M-ary source into multiple bitplanes which are then compressed by a single binary low-density parity-check (LDPC) code. Though the inter-bitplane correlation of M-ary sources can be exploited at the decoder by the joint-bitplane belief propagation (JBBP) algorithm, accurate online estimation of varying local source correlation still remains a major challenge. To tackle this problem, this paper proposes an M-ary counterpart of the sliding-window belief propagation (SWBP) algorithm to realize simultaneous source recovery and correlation estimation. To search for the optimal sliding-window size, the expected rate is raised as a new criterion. Moreover, an adaptive method is proposed to decide whether correlation reestimation is necessary. The M-ary SWBP (MSWBP) algorithm is then generalized to obtain its 2D form, which can be used to tackle the ASWC of 2D M-ary sources with nonstationary correlation. The developed 1D/2D-MSWBP algorithm inherits all merits of the original binary SWBP algorithm, e.g., near-optimal coding efficiency, low complexity, insensitivity to initial settings, etc., making it a very attractive technique in practice.