Comparison and Analysis of Four Signal Detection Algorithms in Different MIMO-VLC Systems

Chong Li, Yufeng Shao, An-rong Wang, Peng-Ying Chen, Yanlin Li, Renjie Zuo, Shuanfan Liu, J. Yuan
{"title":"Comparison and Analysis of Four Signal Detection Algorithms in Different MIMO-VLC Systems","authors":"Chong Li, Yufeng Shao, An-rong Wang, Peng-Ying Chen, Yanlin Li, Renjie Zuo, Shuanfan Liu, J. Yuan","doi":"10.1109/ICCECE58074.2023.10135532","DOIUrl":null,"url":null,"abstract":"In indoor high-speed visible light communication (VLC) systems, the detection sensitivities of several access signals are often affected due to the mutual interference of different light-emitting diodes (LED) emission signals and the multipath effect from different transmission channels, which hinders the wide application of multiple-input multiple-output-VLC(MIMO-VLC) technology. In this work, high speed VLC signal using 16 quadrature amplitude modulation (16QAM) modulation format is selected, and four signal detection algorithms are compared and analyzed in different MIMO-VLC systems. The results show that the bit error rate (BER) performance while suing zero forcing-successive interference cancellation (SIC-ZF) is significantly better than that of ZF and minimum mean square error (MMSE) signal detection algorithms in complex indoor environments. At the SNR $\\mathbf{\\leqslant 10dB}$ case, the value of BER in 4×6 MIMO system can reach 10−5 using SIC-ZF ignoring impacts of non-line-of-sight (NLOS) links.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCECE58074.2023.10135532","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

In indoor high-speed visible light communication (VLC) systems, the detection sensitivities of several access signals are often affected due to the mutual interference of different light-emitting diodes (LED) emission signals and the multipath effect from different transmission channels, which hinders the wide application of multiple-input multiple-output-VLC(MIMO-VLC) technology. In this work, high speed VLC signal using 16 quadrature amplitude modulation (16QAM) modulation format is selected, and four signal detection algorithms are compared and analyzed in different MIMO-VLC systems. The results show that the bit error rate (BER) performance while suing zero forcing-successive interference cancellation (SIC-ZF) is significantly better than that of ZF and minimum mean square error (MMSE) signal detection algorithms in complex indoor environments. At the SNR $\mathbf{\leqslant 10dB}$ case, the value of BER in 4×6 MIMO system can reach 10−5 using SIC-ZF ignoring impacts of non-line-of-sight (NLOS) links.
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
四种信号检测算法在不同MIMO-VLC系统中的比较与分析
在室内高速可见光通信(VLC)系统中,由于不同发光二极管(LED)发射信号的相互干扰和不同传输通道的多径效应,常常影响多个接入信号的检测灵敏度,阻碍了多输入多输出VLC(MIMO-VLC)技术的广泛应用。本文选择了采用16正交调幅(16QAM)调制格式的高速VLC信号,并对不同MIMO-VLC系统中的四种信号检测算法进行了比较和分析。结果表明,在复杂的室内环境中,采用零强制-逐次干扰抵消(SIC-ZF)的误码率(BER)性能明显优于ZF和最小均方误差(MMSE)信号检测算法。在信噪比$\mathbf{\leqslant 10dB}$情况下,使用SIC-ZF忽略非视距(NLOS)链路的影响,4×6 MIMO系统的误码率可以达到10−5。
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
Clutter Edge and Target Detection Method Based on Central Moment Feature Adaptive short-time Fourier transform based on reinforcement learning Design and implementation of carrier aggregation and secure communication in distribution field network Power data attribution revocation searchable encrypted cloud storage Research of Intrusion Detection Based on Neural Network Optimized by Sparrow Search Algorithm
×
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