arrow
返回

Construction of Polar Codes Based on Memetic Algorithm

delete2023-10-01
delete0
PRE
AI
Л
Линг Лиу
W
wenhao yuan
Z
Zhengping Liang
马晓亮 (Xiaoliang Ma)
朱泽轩 封面图
朱泽轩 (Zexuan Zhu) *
DOI:10.1109/TETCI.2023.3234564delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
As an emerging coding technique chosen by the 5th generation wireless systems (5G) standardization process, polar coding has attracted the attention of both academia and industry in recent years. The currently used construction methods of polar code are generally based on the reliability of each polarized sub-channel, which directly correspond to the Successive Cancellation (SC) decoding algorithm. However, much less is known about the optimal construction of polar codes under more sophisticated decoding methods such as the Successive Cancellation List (SCL) decoding. There is currently no perfect theory to derive the optimal construction for the SCL decoding to the best of our knowledge, because finding such optimal construction of SCL is considered to be a hard problem for normal choices of the list size. To address this problem, in this paper we turn to evolutionary computation, and propose a memetic algorithm by incorporating prior knowledge obtained from both the channel estimation of the SC-profile and the codeword weight evaluation of the RM-profile, shorted as MA-SCRM. The potential constructions of polar codes are expressed as binary sequences which are processed as the individuals of the population in MA-SCRM. Based on the prior knowledge obtained from the SC-profile and the Reed-Muller-profile, we design special initialization and evolutional operators for polar codes construction. An elitism archive is also introduced to maintain promising constructions and accelerate the convergence of the algorithm. For the SCL decoding, MA-SCRM obtains polar-coding constructions that are more excellent than the SC decoder construction in the sense of block error probability. Compared with the SC decoding construction method, MA-SCRM can reduce the block error probability by up to 48.78% for the original block error rate around 10(-2), and more improvement can be observed for lower original block error rate.
Keyword:
Construction
evolutionary computation
memetic algorithm
polar codes
SCL decoding

期刊

I
IEEE Transactions on Emerging Topics in Computational Intelligence
IF:
6.5
论文数:
1.4K
被引数:
4.5K

机构

S
shenzhen university
学者数:
4.6W
论文数: 3.4W
被引数: 72
引用论文

引用论文

Reactivity of phosphonodithioato NiII complexes: solution equilibria, solid state studies and theoretical calculations on the adduct formation with some pyridine derivatives†
err2001-01-01
err0
PREAI
errM. Carla Aragoni; Massimiliano Arca; Francesco Demartin; Francesco A. Devillanova; Claudia Graiff; Francesco Isaia; Vito Lippolis; Antonio Tiripicchio; Gaetano Verani
err分享
err收藏
err分享
err收藏
Low-Complexity Construction of Polar Codes Based on Genetic Algorithm
err2021-10-01
err11
errOAAI
errZhou, Huayi; Gross, Warren J.; Zhang, Zaichen; You, Xiaohu; Zhang, Chuan
err分享
err收藏
err分享
err收藏
An evaluation of hydrometric monitoring across the Canadian pan-Arctic region, 1950–2008
err2011-12-01
err0
errOAAI
errTheo J. Mlynowski; Marco A. Hernández-Henríquez; Stephen J. Déry
err分享
err收藏
AI Coding: Learning to Construct Error Correction Codes
err2020-01-01
err58
errOAAI
errHuang, Lingchen; Zhang, Huazi; Li, Rong; Ge, Yiqun; Wang, Jun
err分享
err收藏
学者 查看更多内容