Joint source-channel list sequence decoding

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. Based on these performance improvements, we propose a joint source-channel LS decoding scheme. The scheme is based on the Max-Log List Algorithm for simultaneous soft symbol and LS decoding of convolutional codes. In existing systems where a cyclic redundancy check for error mitigation is concatenated with a convolutional code for error correction, this scheme can be implemented in a fully backward compatible receiver.