Informed dynamic scheduling strategies for novel majority-logic decoding of non-binary LDPC codes

Recent studies show that dynamic scheduling using the latest available information is superior to the flooding scheduling. While the existing works on informed dynamic scheduling focus on belief propagation (BP) based algorithm for binary LDPC codes, in this paper we devise novel methods which are appropriate for majority-logic decoding of non-binary LDPC codes. Firstly we propose a low complexity extrinsic message based decoding algorithm for non-binary LDPC codes. The novelty of this decoding algorithm lies in that we compute extrinsic messages and iteratively update the messages in every iteration. Then we propose a dynamic scheduling schemes specifically designed for majority-logic decoding of non-binary LDPC codes. The proposed scheduling method, named informed dynamic scheduling, can achieve better performance compared with the layered and the flooding schemes.