A mixed MAP/MLSE receiver for convolutional coded signals transmitted over a fading channel

This paper addresses the problem of estimating a rapidly fading convolutionally coded signal such as might be found in a wireless telephony or data network. We model both the channel gain and the convolutionally coded signal as Markov processes, and thus the noisy received signal as a hidden Markov process (HMP). Two now-classical methods for estimating finite-state hidden Markov processes are the Viterbi algorithm and the a posteriori probability (APP) filter. A hybrid recursive estimation procedure is derived whereby one hidden process (the encoder state in our application) is estimated using a Viterbi-type (ie sequence based) cost and the other (the fading process) using an APP based cost such as maximum a postetiori probability. Using simulations, the performance of the optimal scheme is compared with a number of suboptimal techniques-decision directed Kalman and HMP predictors, and Kalman filter and HMP filter per-survivour processing (PSP) techniques. Superior performance of the optimal scheme is demonstrated with little extra computational requirement compared to the PSP techniques