Compressive Sensing Based Channel Estimation for High-order MIMO Systems

Zhiguo Lv, Y. Li
{"title":"Compressive Sensing Based Channel Estimation for High-order MIMO Systems","authors":"Zhiguo Lv, Y. Li","doi":"10.3991/IJOE.V14I07.8218","DOIUrl":null,"url":null,"abstract":"The high-order multiple-input multiple-output (MIMO) system can remarkably increase the data rate or enhance the reliability. However, it is difficult to perform channel estimation because of the massive number of antennas. The Narrow Band Estimation Antenna Processing (NBEAP) scheme is used to deal with this issue. Nevertheless, the accuracy of the channel estimation needs to be improved. In this paper, a compressive sensing based scheme named Narrow Band Estimation Fixed Antenna Processing (NBEFAP) is proposed to estimate the channel state information (CSI) for high-order MIMO systems. A simple pilot structure is designed to decrease the computation complexity. In addition, the pilot length is adjusted according to the time-varying sparsity level of the CSI. Compared with NBEAP scheme, NBEFAP scheme can improve the estimation error performance. Simulation results verify the effectiveness of the NBEFAP scheme.","PeriodicalId":387853,"journal":{"name":"Int. J. Online Eng.","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Online Eng.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3991/IJOE.V14I07.8218","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

The high-order multiple-input multiple-output (MIMO) system can remarkably increase the data rate or enhance the reliability. However, it is difficult to perform channel estimation because of the massive number of antennas. The Narrow Band Estimation Antenna Processing (NBEAP) scheme is used to deal with this issue. Nevertheless, the accuracy of the channel estimation needs to be improved. In this paper, a compressive sensing based scheme named Narrow Band Estimation Fixed Antenna Processing (NBEFAP) is proposed to estimate the channel state information (CSI) for high-order MIMO systems. A simple pilot structure is designed to decrease the computation complexity. In addition, the pilot length is adjusted according to the time-varying sparsity level of the CSI. Compared with NBEAP scheme, NBEFAP scheme can improve the estimation error performance. Simulation results verify the effectiveness of the NBEFAP scheme.
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
基于压缩感知的高阶MIMO系统信道估计
高阶多输入多输出(MIMO)系统可以显著提高数据速率或提高可靠性。然而,由于天线数量庞大,信道估计非常困难。窄带估计天线处理(NBEAP)方案用于解决这一问题。然而,信道估计的精度还有待提高。提出了一种基于压缩感知的窄带估计固定天线处理(NBEFAP)方案,用于估计高阶MIMO系统的信道状态信息(CSI)。设计了简单的导频结构,降低了计算复杂度。此外,导频长度根据CSI的时变稀疏程度进行调整。与NBEAP方案相比,NBEAP方案可以提高估计误差的性能。仿真结果验证了NBEFAP方案的有效性。
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
Infrared-based Short-Distance FSO Sensor Network System Real-Time Image Transmission Algorithm in WSN with Limited Bandwidth Path Planning for Unmanned Underwater Vehicle Based on Improved Particle Swarm Optimization Method Computer Assisted E-Laboratory using LabVIEW and Internet-of-Things Platform as Teaching Aids in the Industrial Instrumentation Course Towards Simulation Aided Online Teaching: Material Design for Applied Fluid Mechanics
×
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