Performance bounds and codes design criteria for channel decoding with a-priori information

In this article we focus on the channel decoding problem in presence of a-priori information. In particular, assuming that the a-priori information reliability is not perfectly estimated at the receiver, we derive a novel analytical framework for evaluating the decoder's performance. It is derived the important result that a good code, i.e., a code which allows to fully exploit the potential benefit of a-priori information, must associate information sequences with high Hamming distances to codewords with low Hamming distances. Basing on the proposed analysis, we analyze the performance of random codes and turbo codes.