基于机器学习的信道估计

Yue Zhu, Gongpu Wang, F. Gao
{"title":"基于机器学习的信道估计","authors":"Yue Zhu, Gongpu Wang, F. Gao","doi":"10.1049/PBTE081E_CH4","DOIUrl":null,"url":null,"abstract":"Wireless communication has been a highly active research field. Channel estimation technology plays a vital role in wireless communication systems. Channel estimates are required by wireless nodes to perform essential tasks such as precoding, beamforming, and data detection. A wireless network would have good performance with well-designed channel estimates. In this chapter, we first review the channel model for wireless communication systems and then describe two traditional channel estimation methods, and finally introduce two newly designed channel estimators based on deep learning and one expectation-maximization-based channel estimator.","PeriodicalId":358911,"journal":{"name":"Applications of Machine Learning in Wireless Communications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Machine-learning-based channel estimation\",\"authors\":\"Yue Zhu, Gongpu Wang, F. Gao\",\"doi\":\"10.1049/PBTE081E_CH4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wireless communication has been a highly active research field. Channel estimation technology plays a vital role in wireless communication systems. Channel estimates are required by wireless nodes to perform essential tasks such as precoding, beamforming, and data detection. A wireless network would have good performance with well-designed channel estimates. In this chapter, we first review the channel model for wireless communication systems and then describe two traditional channel estimation methods, and finally introduce two newly designed channel estimators based on deep learning and one expectation-maximization-based channel estimator.\",\"PeriodicalId\":358911,\"journal\":{\"name\":\"Applications of Machine Learning in Wireless Communications\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applications of Machine Learning in Wireless Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1049/PBTE081E_CH4\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applications of Machine Learning in Wireless Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/PBTE081E_CH4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

无线通信一直是一个非常活跃的研究领域。信道估计技术在无线通信系统中起着至关重要的作用。无线节点需要信道估计来执行基本任务,如预编码、波束形成和数据检测。设计良好的信道估计会使无线网络具有良好的性能。在本章中,我们首先回顾了无线通信系统的信道模型,然后描述了两种传统的信道估计方法,最后介绍了两种新设计的基于深度学习的信道估计器和一种基于期望最大化的信道估计器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine-learning-based channel estimation
Wireless communication has been a highly active research field. Channel estimation technology plays a vital role in wireless communication systems. Channel estimates are required by wireless nodes to perform essential tasks such as precoding, beamforming, and data detection. A wireless network would have good performance with well-designed channel estimates. In this chapter, we first review the channel model for wireless communication systems and then describe two traditional channel estimation methods, and finally introduce two newly designed channel estimators based on deep learning and one expectation-maximization-based channel estimator.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信