Joint Source-Channel List Sequence Decoding

Abstract:  In this paper we evaluate the performance of list sequence (LS) maximum a posteriori probability (MAP) decoding on the additive white Gaussian noise (AWGN) channel and the fully interleaved flat Rayleigh fading channel. In particular, we focus on the frame error rate (FER) of LS-MAP decoding with genie-assisted error detection. It is demonstrated that LS-MAP decoding yields significant performance improvements relative to single sequence MAP decoding on the AWGN channel as well as the fully interleaved flat Rayleigh fading channel. Furthermore, feedback convolutional codes have been observed to have the potential to yield improved FER performance with both single sequence MAP and LS-MAP decoding, compared to feedforward convolutional codes.