Soft decoding employing algebraic decoding beyond eBCH

Soft decoding of binary codes based on algebraic decoding is treated. The algebraic decoder generates all error patterns up to a given weight higher than the designed error correcting capability e_BCH. The performance of different soft decoders employing such algebraic decoding is investigated and compared with hard decoding, the Chase second algorithm and soft maximum likelihood decoding. Furthermore, we propose an iterative decoder using an acceptance criteria to determine if we have found the maximum likelihood decision estimate. The acceptance criteria ensures a low average decoding complexity and by iterative decoding, performance close to that of maximum likelihood decoding is obtained