Joint source channel coding and estimation of hidden Markov structures

We describe techniques for joint source-channel coding of hidden Markov sources using a modified turbo decoding algorithm. This avoids the need to perform any explicit source coding prior to transmission, and instead allows the decoder to utilize the a priori structure due to the hidden Markov source. In addition, we present methods that allow the decoder to estimate the parameters of the Markov model. In combination, these techniques allow the decoder to identify, estimate, and exploit the source structure. The estimation does not degrade the performance of the system, i.e. the joint estimation/decoding allows convergence at the same noise levels as a system in which the decoder has perfect a priori knowledge of the source parameters. Similar ideas can be successfully applied for the case of hidden Markov channels and combined turbo decoding-equalization for ISI channels.