A Computationally Efficient Least Squares Channel Estimation Method for MIMO-OFDM Systems

Ahmad Hasan, S. Motakabber, F. Anwar, M. H. Habaebi, M. Ibrahimy
{"title":"A Computationally Efficient Least Squares Channel Estimation Method for MIMO-OFDM Systems","authors":"Ahmad Hasan, S. Motakabber, F. Anwar, M. H. Habaebi, M. Ibrahimy","doi":"10.1109/ICCCE50029.2021.9467142","DOIUrl":null,"url":null,"abstract":"The 5th generation of cellular system is expected to incur a huge traffic rise which would necessitate the adoption of an estimation method that is efficient but at the same time practical through easy implementation. Some of the most popular methods used in cellular communication for channel estimation are the Least Squares (LS) algorithm and the Minimum Mean Square Error (MMSE) algorithm. Both of them has their own merits and limitations. While LS estimation is simple to adopt and resource-friendly, its performance is par to MMSE, which requires channel statistics and is thus more impractical for the industry. In this paper, an efficient LS estimation method is proposed by minimising relative error or difference between each estimated channel coefficient from its actual value, which is often overlooked when considering overall error. It’s in turn, reduces the error per bit and eventually induces faster processing of data. Results on the proposed algorithm are demonstrated via bit error rate and mean square error comparison.","PeriodicalId":122857,"journal":{"name":"2021 8th International Conference on Computer and Communication Engineering (ICCCE)","volume":"476 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 8th International Conference on Computer and Communication Engineering (ICCCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCE50029.2021.9467142","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 5th generation of cellular system is expected to incur a huge traffic rise which would necessitate the adoption of an estimation method that is efficient but at the same time practical through easy implementation. Some of the most popular methods used in cellular communication for channel estimation are the Least Squares (LS) algorithm and the Minimum Mean Square Error (MMSE) algorithm. Both of them has their own merits and limitations. While LS estimation is simple to adopt and resource-friendly, its performance is par to MMSE, which requires channel statistics and is thus more impractical for the industry. In this paper, an efficient LS estimation method is proposed by minimising relative error or difference between each estimated channel coefficient from its actual value, which is often overlooked when considering overall error. It’s in turn, reduces the error per bit and eventually induces faster processing of data. Results on the proposed algorithm are demonstrated via bit error rate and mean square error comparison.
一种计算效率高的MIMO-OFDM系统最小二乘信道估计方法
预计第五代蜂窝系统将产生巨大的流量增长,这将需要采用一种高效但同时又易于实现的实用估计方法。蜂窝通信中最常用的信道估计方法是最小二乘(LS)算法和最小均方误差(MMSE)算法。两者都有各自的优点和局限性。虽然LS估计易于采用且资源友好,但其性能与MMSE相当,而MMSE需要信道统计,因此对行业来说更加不切实际。本文提出了一种有效的信道系数估计方法,将信道系数估计值与实际值之间的相对误差或差值最小化,这在考虑整体误差时往往被忽略。反过来,它减少了每比特的错误,并最终导致更快的数据处理。通过误码率和均方误差比较验证了算法的有效性。
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 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:604180095
Book学术官方微信