Parallel Implementation of the CCSDS Turbo Decoder on GPU  

作　　者：Liu Zhanxian Liu Rongke Zhang Haijun Wang Ning Sun Lei Wang Jianquan 

机构地区：[1]School of Computer&Communication Engineering,University of Science and Technology Beijing,Beijing 100083,China [2]School of Electronic and Information Engineering,Beihang University,Beijing 100191,China [3]Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services,Institute of Artificial Intelligence,University of Science and Technology Beijing,Beijing 100083,China [4]School of Information Engineering,Zhengzhou University,Zhengzhou 450001,China [5]School of Automation and Electrical Engineering,University of Science and Technology Beijing,Beijing 100083,China

出　　处：《China Communications》2024年第10期70-77,共8页中国通信（英文版）

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

摘　　要：This paper presents a software turbo decoder on graphics processing units(GPU).Unlike previous works,the proposed decoding architecture for turbo codes mainly focuses on the Consultative Committee for Space Data Systems(CCSDS)standard.However,the information frame lengths of the CCSDS turbo codes are not suitable for flexible sub-frame parallelism design.To mitigate this issue,we propose a padding method that inserts several bits before the information frame header.To obtain low-latency performance and high resource utilization,two-level intra-frame parallelisms and an efficient data structure are considered.The presented Max-Log-Map decoder can be adopted to decode the Long Term Evolution(LTE)turbo codes with only small modifications.The proposed CCSDS turbo decoder at 10 iterations on NVIDIA RTX3070 achieves about 150 Mbps and 50Mbps throughputs for the code rates 1/6 and 1/2,respectively.

关 键 词：CCSDS CUDA GPU parallel decoding turbo codes 

分 类 号：TN911.2[电子电信—通信与信息系统]