Low-complexity Decoding Method of Generalized LDPC with Polar Component Codes

Generalized low-density parity-check with polar component (GLDPC-PC) codes exhibit promising potential for 6G wireless systems with higher demands on reliability and data rate. The decoding method for GLDPC-PC codes involves belief propagation (BP), where the soft information of the component code is used as extrinsic information for check nodes. Although the Bahl-Cocke-Jelinek-Raviv (BCJR) decoding algorithm provides bitwise optimal soft information for linear block codes, its decoding complexity increases exponentially with the code length, making it impractical for applications. Therefore, the near-optimal soft-output successive cancellation list (SO-SCL) decoding with fixed scaling is proposed to reduce decoding complexity. However, the complexity of SO-SCL decoding still holds potential for further optimization. In this work, we propose an offline approximation of the unvisited probability codebook and a staged scaling strategy for the extrinsic information to reduce decoding complexity while maintaining low performance loss.