Joint Decoding and Estimation of S patio-Temporally Correlated Binary Sources

Abstract

In the context of distributed joint source-channel coding, we conceive a joint decoding and estimation scheme for binary Markov sources exhibiting spatio-temporal correlation. The proposed scheme is designed based on the serial concatenation of a trellis coded modulation (TCM) scheme and a unity-rate code. The symbol-based maximum a posteriori algorithm employed for TCM decoding is modified in order to exploit the source correlation. The estimation of both the spatial and temporal correlation parameters is performed jointly with the iterative decoding, hence allowing the estimated parameters to be updated after each iteration. Our simulation results reveal that when both the spatial and temporal correlation parameters are unknown, the proposed joint decoding and estimation scheme approaches the performance to the ideal system relying on perfectly known correlation parameters, therefore, demonstrating the superiority of the proposed scheme.