A successive decoding strategy for channels with memory

This paper presents both an information lossless coding scheme and a method to evaluate constrained capacity for channels with memory and unknown state. The fundamental idea is to decompose the original channel into a bank of memoryless sub-channels with partially known states, then successively decode these sub-channels. The receiver of each sub-channel consists of an optimal estimator followed by a memoryless channel decoder. The coding scheme translates the codes and decoders designed for memoryless channels with near capacity performance to channels with memory. The results are applied to both finite state Markov channels and correlated flat fading channels