Hybrid Beamforming Based on Dictionary Learning for Millimeter Wave MIMO System

Li Zhu, Jiang Zhu, Shilian Wang, Li Hu, Qian Cheng
{"title":"Hybrid Beamforming Based on Dictionary Learning for Millimeter Wave MIMO System","authors":"Li Zhu, Jiang Zhu, Shilian Wang, Li Hu, Qian Cheng","doi":"10.1109/VTCFall.2019.8891555","DOIUrl":null,"url":null,"abstract":"Hybrid beamforming in transmitter and receiver can improve the spectral efficiency of millimeterwave (mmWave) multiple-input multiple-output (MIMO) communication system significantly, and can reduce the complexity of communication system. However, when the number of transmitted data streams is large, the existing designing schemes of hybrid beamforming, such as sparse approximation by orthogonal matching pursuit(OMP) algorithm, suffer from performance degradation. In this paper, we propose dictionary learning (DL) algorithm to perform the design of hybrid beamforming for mmWave MIMO system. Simulation result shows that the spectral efficiency of hybrid beamforming based on DL approaches that of optimal beamforming without constraint, which is far superior to the spectral efficiency of hybrid beamforming based on OMP. Moreover, the convergence property of the proposed algorithm is also verified.","PeriodicalId":6713,"journal":{"name":"2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall)","volume":"15 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VTCFall.2019.8891555","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Hybrid beamforming in transmitter and receiver can improve the spectral efficiency of millimeterwave (mmWave) multiple-input multiple-output (MIMO) communication system significantly, and can reduce the complexity of communication system. However, when the number of transmitted data streams is large, the existing designing schemes of hybrid beamforming, such as sparse approximation by orthogonal matching pursuit(OMP) algorithm, suffer from performance degradation. In this paper, we propose dictionary learning (DL) algorithm to perform the design of hybrid beamforming for mmWave MIMO system. Simulation result shows that the spectral efficiency of hybrid beamforming based on DL approaches that of optimal beamforming without constraint, which is far superior to the spectral efficiency of hybrid beamforming based on OMP. Moreover, the convergence property of the proposed algorithm is also verified.
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
基于字典学习的毫米波MIMO系统混合波束形成
发射端和接收端的混合波束形成技术可以显著提高毫米波(mmWave)多输入多输出(MIMO)通信系统的频谱效率,降低通信系统的复杂度。然而,当传输数据流数量较大时,现有的混合波束形成设计方案,如正交匹配追踪稀疏逼近算法(OMP),存在性能下降的问题。在本文中,我们提出了字典学习(DL)算法来进行毫米波MIMO系统的混合波束形成设计。仿真结果表明,基于DL的混合波束形成的频谱效率接近无约束的最优波束形成,远优于基于OMP的混合波束形成的频谱效率。此外,还验证了该算法的收敛性。
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
Towards Emergency Braking as a Fail-Safe State in Platooning: A Simulative Approach Online Task Offloading with Bandit Learning in Fog-Assisted IoT Systems Hybrid Localization: A Low Cost, Low Complexity Approach Based on Wi-Fi and Odometry Residual Energy Optimization for MIMO SWIPT Two-Way Relaying System Traffic Forecast in Mobile Networks: Classification System Using Machine Learning
×
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:481959085
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