Optimization and Improvement of BP Decoding Algorithm for Polar Codes Based on Deep Learning

Li Ge, Guiping Li
{"title":"Optimization and Improvement of BP Decoding Algorithm for Polar Codes Based on Deep Learning","authors":"Li Ge, Guiping Li","doi":"10.2478/ijanmc-2023-0057","DOIUrl":null,"url":null,"abstract":"Abstract In order to solve the high latency problem of polar codes belief propagation decoding algorithm in the 5G and the dimension limitation problem of belief propagation decoding algorithm under deep learning, a multilayer perceptron belief propagation decoding (MLP-BP) algorithm based on partitioning idea is proposed. In this work, polar codes is decoded using neural networks in partitioning, and the right transfer message value of BP decoding algorithm is also set to complete the propagation process. Simulation results show that, compared with BP decoding algorithm, the proposed algorithm has better decoding performance, reducing the decoding latency, and it is also applicable to long polar codes.","PeriodicalId":193299,"journal":{"name":"International Journal of Advanced Network, Monitoring and Controls","volume":"38 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Advanced Network, Monitoring and Controls","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/ijanmc-2023-0057","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Abstract In order to solve the high latency problem of polar codes belief propagation decoding algorithm in the 5G and the dimension limitation problem of belief propagation decoding algorithm under deep learning, a multilayer perceptron belief propagation decoding (MLP-BP) algorithm based on partitioning idea is proposed. In this work, polar codes is decoded using neural networks in partitioning, and the right transfer message value of BP decoding algorithm is also set to complete the propagation process. Simulation results show that, compared with BP decoding algorithm, the proposed algorithm has better decoding performance, reducing the decoding latency, and it is also applicable to long polar codes.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于深度学习的BP极码译码算法优化与改进
摘要为了解决5G条件下极性码信念传播译码算法的高延迟问题和深度学习条件下信念传播译码算法的维数限制问题,提出了一种基于分块思想的多层感知器信念传播译码(MLP-BP)算法。在本工作中,利用神经网络对极坐标码进行分块解码,并设置BP解码算法的正确传递消息值,完成传播过程。仿真结果表明,与BP译码算法相比,该算法具有更好的译码性能,降低了译码延迟,也适用于长极码。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Automatic Landing Control of Aircraft Based on Cognitive Load Theory and DDPG Research on Simulation Approximate Solution Strategy for Complex Kinematic Models Indoor Robot SLAM with Multi-Sensor Fusion Securing Operating Systems (OS): A Comprehensive Approach to Security with Best Practices and Techniques Lightweight Low-Altitude UAV Object Detection Based on Improved YOLOv5s
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1