Improved Iterative Convergence Rate for Soft-Decision Bit-Level Reed-Solomon Decoders using Information Set Decoding

摘要

Iterative bit-level decoders for Reed-Solomon codes, such as the ABP and the PTA, have been shown in literature to yield a good error correction performance. However, this is often at the cost of a high computational complexity. This complexity can be attributed to the number of iterations required during the decoding process. This paper focuses on improving the iterative convergence rate of the bit-level decoders with aid of an additional stopping criteria based on information set decoding techniques. The additional stopping criteria is able to reduce the number of iterations by obtaining an information set and using it to decode the entire received vector. This decoding approach significantly reduces the number of iterations required during decoding of the received vector, while still maintaining the good error correction performance of iterative bit-level decoders.