Low-complexity recursive convolutional precoding for OFDM-based large-scale antenna systems

Yinsheng Liu, Geoffrey Ye Li
{"title":"Low-complexity recursive convolutional precoding for OFDM-based large-scale antenna systems","authors":"Yinsheng Liu, Geoffrey Ye Li","doi":"10.1109/ICASSP.2016.7472303","DOIUrl":null,"url":null,"abstract":"Large-scale antenna (LSA) has gained a lot of attention recently since it can significantly improve the performance of wireless systems. Similar to multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) or MIMO-OFDM, LSA can be also combined with OFDM to deal with frequency selectivity in wireless channels. However, such combination suffers from substantially increased complexity proportional to the number of antennas in LSA systems. In this paper, we propose a low-complexity recursive convolutional pre-coding to address the issues above. The traditional ZF precoding is implemented through the recursive convolutional precoding in the time domain so that only one IFFT is required for each user and the matrix inversion can be also avoided. Simulation results show that the proposed approach can achieve the same performance as that of ZF but with much lower complexity.","PeriodicalId":165321,"journal":{"name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2016.7472303","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Large-scale antenna (LSA) has gained a lot of attention recently since it can significantly improve the performance of wireless systems. Similar to multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) or MIMO-OFDM, LSA can be also combined with OFDM to deal with frequency selectivity in wireless channels. However, such combination suffers from substantially increased complexity proportional to the number of antennas in LSA systems. In this paper, we propose a low-complexity recursive convolutional pre-coding to address the issues above. The traditional ZF precoding is implemented through the recursive convolutional precoding in the time domain so that only one IFFT is required for each user and the matrix inversion can be also avoided. Simulation results show that the proposed approach can achieve the same performance as that of ZF but with much lower complexity.
基于ofdm的大规模天线系统的低复杂度递归卷积预编码
大型天线(large - large antenna, LSA)由于能够显著提高无线系统的性能,近年来受到了广泛的关注。与多输入多输出(MIMO)正交频分复用(OFDM)或MIMO-OFDM类似,LSA也可以与OFDM相结合来处理无线信道中的频率选择性。然而,这种组合的复杂性与LSA系统中天线的数量成正比。在本文中,我们提出了一种低复杂度递归卷积预编码来解决上述问题。传统的ZF预编码是通过时域递归卷积预编码来实现的,这样每个用户只需要一个IFFT,也可以避免矩阵反转。仿真结果表明,该方法可以达到与ZF算法相同的性能,但复杂度要低得多。
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