A parallel MAP algorithm for low latency turbo decoding

To reduce the computational decoding delay of turbo codes, we propose a parallel algorithm for maximum a posteriori (MAP) decoders. We divide a whole noisy codeword into sub-blocks and use multiple processors to perform sub-block MAP decoding in parallel. Unlike the previously proposed approach with sub-block overlapping, we utilize the forward and backward variables computed in the previous iteration to provide boundary distributions for each sub-block MAP decoder. Our scheme depicts asymptotically optimal performance in the sense that the BER is the same as that of the regular turbo decoder.