Estimation and decoding strategies for channels with abruptly changing statistics

This paper proposes iterative estimation and decoding techniques for memoryless channels with a bounded number of abrupt changes in channel statistics. Specifically, the channel under consideration is a binary symmetric channel with a crossover probability that changes a bounded number of times during the transmission of a codeword; the channel state information to be estimated consists of the crossover probabilities of the different segments and the location(s) of the transition point(s). To estimate the transition points, a technique developed for source coding of piecewise-stationary memoryless sources is adapted; then the expectation-maximization algorithm is used to estimate the crossover probabilities. This segmentation/estimation is carried out on the error sequence of the currently hypothesized frame. Simulation results using turbo codes indicate that the proposed receiver performs almost as well as a receiver that has perfect knowledge of the channel.