A new iterative soft-decision decoding algorithm using list decoding of minimum weight sub-trellis search

摘要

Iterative decoding algorithm using minimum weight sub-trellis search, which is one of minimum distance search (MDS), has been proposed by Koumoto et al. Their decoding algorithm achieve not only almost optimum error performance with for all Reed-Muller(RM) codes and extended BCH(EBCH) codes of length 64 but also near optimum for the (128, 29) and the (128, 36) EBCH code with a drastic reduction of decoding complexity. In this paper, we present a new iterative soft-decision decoding algorithm using efficient MDS algorithm. In the proposed decoding algorithm, to make improvement of error performance, we devise two methods, (1) which improve the quality of initial candidate codewords and (2) in the case previously generated codewords appear twice in iterative decoding, instead of finishing decoding, continue decoding by using list decoding of MDS. The simulation results show that the proposed decoding algorithm achieves near error performance with MLD for any RM codes of length 128 and practically optimum for the (256, 37), (256, 93) and (256, 163) RM codes.