Reliability-based information set decoding of binary linear block codes
In this paper, soft decision decoding of linear block codes bared on the reprocessing of several information sets is considered. These information sets are chosen according to the reliability measures of the received symbols and constructed from the most reliable information set, referred to as the most reliable basis. Each information set is then reprocessed by a multi-stage decoding algorithm until either the optimum error performance, or a desired level of error performance is achieved. General guidelines for the trade-offs between the number of in formation sets to be processed, the number of computations for reprocessing each information set, and the error performance to be achieved are provided. It is shown that with a proper selection of few information sets, low-complexity near-optimum soft decision decoding of relatively long block codes (64 less than or equal to N less than or equal to 128) can be achieved with significant reduction in computation complexity with respect to other known algorithms. This scheme, which generalizes the reprocessing of the most reliable basis with the ordered statistic algorithm proposed by Fossorier and Lin, is particularly efficient for codes with rate R less than or equal to 1/2.
binary linear block codes soft decision decoding ordered statistics bounded distance decoding