Improved Informed Dynamic Scheduling Strategies for 5G LDPC Codes

In this paper, we propose two new scheduling algorithms to address the issues of existing informed dynamic scheduling (IDS) decoding algorithms of short low-density parity-check (LDPC) codes for the fifth-generation (5G) new radio (NR). The first issue is the complexity problem, where the high complexity of IDS makes hardware implementation difficult. By considering the impact of puncturing for the first two columns of base matrices, the proposed least-punctured and sum-residual-based (LPSRB) algorithm can reduce decoding complexity. The second issue is the significant degradation of decoding performance when the code length is short. By fully utilizing residuals, the proposed novel residual belief propagation (NRBP) algorithm allocates a significant amount of decoding resources to the less convergent edges. Simulation results demonstrate that NRBP achieves better frame error rate (FER) performance for short LDPC codes.