2020 IEEE International Symposium
on Information Theory
21-26 June 2020 • Los Angeles, California, USA
| Paper ID | C.6.5 | ||
| Paper Title | Improved Belief Propagation List Decoding for Polar Codes | ||
| Authors | Binghao Li, Baoming Bai, Min Zhu, Shenyang Zhou, Xidian University, China | ||
| Session | C.6: Polar Codes I | ||
| Presentation | Lecture | ||
| Track | Coding for Communications | ||
| Manuscript | Click here to download the manuscript | ||
| Virtual Presentation | Click here to watch in the Virtual Symposium | ||
| Abstract | In this paper, we present an improved belief propagation list decoding (BPL) for polar codes. Rather than choosing L permuted factor graphs (FGs) at random, we use the upper bounds on the block error propability of polar codes with different permuted FGs as the metric to choose the best L permuted FGs. By observing the bounds of different permuted FGs, we propose a heuristic method to reduce search complexity. Simulation results show that there is only a gap of 0.2 dB between the frame error rate (FER) performance of the improved BPL decoder using RM16-GA construction and that of length-1024 5G polar code decoded by SCL with the same list size of 32 at FER = 10^−4, but with proposed factor graph selection method, BPL can reduce clock cycles by 97.74% compared with the SCL decoding. | ||
Plan Ahead
2021 IEEE International Symposium on Information Theory
11-16 July 2021 | Melbourne, Victoria, Australia
