This study focuses on the efficiency of message-passing-based decoding algorithms for polar and low-density parity-check (LDPC) codes. Both successive cancellation (SC) and belief propagation (BP) decoding algorithms are studied under the message-passing framework. Counter-intuitively, SC decoding demonstrates the highest decoding efficiency, although it was considered a weak decoder regarding error-correction performance. We analyze the complexity-performance tradeoff to dynamically track the decoding efficiency, where the complexity is measured by the number of messages passed (NMP), and the performance is measured by the statistical distance to the maximum a posteriori (MAP) estimate. This study offers new insight into the contribution of each message passing in decoding, and compares various decoding algorithms on a message-by-message level. The analysis corroborates recent results on terabits-per-second polar SC decoders, and might shed light on better scheduling strategies.
Publication:
2022 IEEE Global Communications Conference (GLOBECOM)
Authors:
Dawei Yin
Shandong University；Huawei Technologies Co. Ltd.
Yuan Li
University of Chinese Academy of Sciences; Academy of Mathematics and Systems Science; Huawei Technologies Co. Ltd.
Xianbin Wang
Huawei Technologies Co. Ltd.
Jiajie Tong
Huawei Technologies Co. Ltd.
Huazi Zhang
Huawei Technologies Co. Ltd.
Jun Wang
Huawei Technologies Co. Ltd.
Guanghui Wang
Shandong University
Guiying Yan
University of Chinese Academy of Sciences; Academy of Mathematics and Systems Science
Email: yangy@amss.ac.cn
Zhiming Ma
University of Chinese Academy of Sciences; Academy of Mathematics and Systems Science
Email: mazm@amt.ac.cn