Belief Propagation List Decoding for Polar Codes:Performance Analysis and Software Implementation on GPU

作     者：Zhanxian Liu Wei Li Lei Sun Wei Li Jianquan Wang Haijun Zhang Zhanxian Liu;Wei Li;Lei Sun;Jianquan Wang;Haijun Zhang

作者机构：School of Computer&Communication EngineeringUniversity of Science and Technology BeijingBeijing 100083China Satellite Frequency and Orbit Resource AgencyState Radio Monitoring CenterBeijing 100041China School of Automation and Electrical EngineeringUniversity of Science and Technology BeijingBeijing 100083China Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous ServicesInstitute of Artificial IntelligenceUniversity of Science and Technology BeijingBeijing 100083China 

出 版 物：《中国通信:英文版》 (China Communications)

年 卷 期：2023年第20卷第9期

页      面：115-126页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the Fundamental Research Funds for the Central Universities (FRF-TP20-062A1) Guangdong Basic and Applied Basic Research Foundation (2021A1515110070) 

主　　题：polar code belief propagation SIMT list decoding GPU 

摘      要：Belief propagation(BP)decoding outputs soft information and can be naturally used in iterative *** list(BPL)decoding provides comparable error-correction performance to the successive cancellation list(SCL)*** this paper,we firstly introduce an enhanced code construction scheme for BPL decoding to improve its errorcorrection ***,a GPU-based BPL decoder with adoption of the new code construction is ***,the proposed BPL decoder is tested on NVIDIA RTX3070 and *** results show that the presented BPL decoder with early termination criterion achieves above 1 Gbps throughput on RTX3070 for the code(1024,512)with 32 lists under good channel conditions.