Exploiting binary Markov channels with unknown parameters in turbo decoding

We describe parallel concatenated codes for communication over binary-input, binary-output hidden Markov channels when the parameters of the Markov channel are unknown a priori. Specifically, we develop a joint estimation/decoding method that allows the estimation of the parameters of the model without the need for training sequences. This method involves little or no sacrifice in performance relative to the case where the Markov channel parameters are provided to the receiver as a priori information. Furthermore,, we show communication at rates which are above the capacity of a memoryless channel with the same stationary bit error probability as the Markov channel, thereby outperforming systems based on the traditional approach of using a channel interleaver to create a channel which is assumed to be memoryless