A wavelet compression based channel feedback protocol for spatially correlated massive MIMO systems

Pengbiao Wang, Junfeng Wang, Cheng-lin Zhao, Xiaokai Liu
{"title":"A wavelet compression based channel feedback protocol for spatially correlated massive MIMO systems","authors":"Pengbiao Wang, Junfeng Wang, Cheng-lin Zhao, Xiaokai Liu","doi":"10.1109/ICT.2015.7124701","DOIUrl":null,"url":null,"abstract":"Equipped with large scale antenna arrays, massive multiple input multiple output systems are qualified with several benefits including enhanced throughput, power efficiency, and anti-interference ability, etc. The acquisition of such advantages requires adequate channel state information at transmitter. In frequency division duplex multiple input multiple output systems, channel state information is extracted through channel feedback mechanism which is not easy to implement due to the fact that the feedback overhead is critical with so many antennas. However, large scale antenna arrays may introduce correlation elements into channel state information due to the limit of the base station size. Therefore, we propose a wavelet compression based channel feedback protocol aiming to reduce the feedback load by exploiting the correlation features among large scale antenna arrays. We take a point-to-point massive multiple input multiple output system into consideration, and both Jakes correlation model and exponential correlation model are applied to make the numerical simulations and verify the performance of the proposed wavelet compression based feedback scheme.","PeriodicalId":375669,"journal":{"name":"2015 22nd International Conference on Telecommunications (ICT)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 22nd International Conference on Telecommunications (ICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICT.2015.7124701","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Equipped with large scale antenna arrays, massive multiple input multiple output systems are qualified with several benefits including enhanced throughput, power efficiency, and anti-interference ability, etc. The acquisition of such advantages requires adequate channel state information at transmitter. In frequency division duplex multiple input multiple output systems, channel state information is extracted through channel feedback mechanism which is not easy to implement due to the fact that the feedback overhead is critical with so many antennas. However, large scale antenna arrays may introduce correlation elements into channel state information due to the limit of the base station size. Therefore, we propose a wavelet compression based channel feedback protocol aiming to reduce the feedback load by exploiting the correlation features among large scale antenna arrays. We take a point-to-point massive multiple input multiple output system into consideration, and both Jakes correlation model and exponential correlation model are applied to make the numerical simulations and verify the performance of the proposed wavelet compression based feedback scheme.
基于小波压缩的空间相关海量MIMO系统信道反馈协议
大规模的多输入多输出系统配备了大规模的天线阵列,具有提高吞吐量、功率效率和抗干扰能力等优点。要获得这些优势,需要在发射机处获得足够的信道状态信息。在频分双工多输入多输出系统中,信道状态信息的提取是通过信道反馈机制实现的,但由于天线数量多,反馈开销很大,实现起来并不容易。然而,由于基站规模的限制,大型天线阵列可能会在信道状态信息中引入相关元素。因此,我们提出了一种基于小波压缩的信道反馈协议,旨在利用大规模天线阵列之间的相关特性来减少反馈负荷。以点对点大规模多输入多输出系统为研究对象,采用Jakes相关模型和指数相关模型进行了数值模拟,验证了所提出的基于小波压缩的反馈方案的性能。
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 求助全文
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