Iterative Soft-Input Soft-Output Bit-Level Reed-Solomon Decoder Based on Information Set Decoding

Abstract

In this paper, a bit-level decoder is presented for soft-input soft-output iterative decoding of Reed-Solomon (RS) codes. The main aim for the development of the proposed algorithm is to reduce the complexity of the decoding process, while yielding a relatively good error correction performance, for the efficient use of RS codes. The decoder utilises information set decoding techniques to reduce the computational complexity cost by lowering the iterative convergence rate during the decoding process. As opposed to most iterative bit-level soft-decision decoders for RS codes, the proposed algorithm is also able to avoid the use of belief propagation in the iterative decoding of the soft bit information, which also contributes to the reduction in the computational complexity cost of the decoding process. The performance of the proposed decoder is investigated when applied to short RS codes. The error correction simulations show the proposed algorithm is able to yield a similar performance to that of the Adaptive Belief Propagation (ABP) algorithm, while being a less complex decoder.