Channel Measurement and Noise Estimation in FBMC/OQAM-Based IoT Networks

Jun Sun, X. Mu, Dejin Kong
{"title":"Channel Measurement and Noise Estimation in FBMC/OQAM-Based IoT Networks","authors":"Jun Sun, X. Mu, Dejin Kong","doi":"10.1155/2022/6518066","DOIUrl":null,"url":null,"abstract":"Channel measurement plays an important role in the emerging 5G-enabled Internet of Things (IoT) networks, which reflects the channel quality and link reliability. In this paper, we address the channel measurement for link reliability evaluation in filter-bank multicarrier with offset quadrature amplitude modulation- (FBMC/OQAM-) based IoT network, which is considered as a promising technique for future wireless communications. However, resulting from the imaginary interference and the noise correlation among subcarriers in FBMC/OQAM, the existing frequency correlation method cannot be directly applied in the FBMC/OQAM-based IoT network. In this study, the concept of the block repetition is applied in FBMC/OQAM. It is demonstrated that the noises among subcarriers are independent by the block repetition and linear combination, instead of correlated. On this basis, the classical frequency correlation method can be applied to achieve the channel measurement. Then, we also propose an advanced frequency correlation method to improve the accuracy of the channel measurement, by assuming channel frequency responses to be quasi-invariant for several successive subcarriers. Simulations are conducted to validate the proposed schemes.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"43 1","pages":"6518066:1-6518066:12"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wirel. Commun. Mob. Comput.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2022/6518066","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

Channel measurement plays an important role in the emerging 5G-enabled Internet of Things (IoT) networks, which reflects the channel quality and link reliability. In this paper, we address the channel measurement for link reliability evaluation in filter-bank multicarrier with offset quadrature amplitude modulation- (FBMC/OQAM-) based IoT network, which is considered as a promising technique for future wireless communications. However, resulting from the imaginary interference and the noise correlation among subcarriers in FBMC/OQAM, the existing frequency correlation method cannot be directly applied in the FBMC/OQAM-based IoT network. In this study, the concept of the block repetition is applied in FBMC/OQAM. It is demonstrated that the noises among subcarriers are independent by the block repetition and linear combination, instead of correlated. On this basis, the classical frequency correlation method can be applied to achieve the channel measurement. Then, we also propose an advanced frequency correlation method to improve the accuracy of the channel measurement, by assuming channel frequency responses to be quasi-invariant for several successive subcarriers. Simulations are conducted to validate the proposed schemes.
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FBMC/ oqam的物联网网络信道测量与噪声估计
信道测量在新兴的5g物联网(IoT)网络中发挥着重要作用,它反映了信道质量和链路可靠性。在本文中,我们讨论了基于滤波组多载波偏移正交调幅(FBMC/OQAM-)的物联网网络中链路可靠性评估的信道测量,这被认为是未来无线通信的一种有前途的技术。然而,由于FBMC/OQAM中存在虚干扰和子载波间的噪声相关,现有的频率相关方法无法直接应用于基于FBMC/OQAM的物联网网络。在本研究中,块重复的概念被应用于FBMC/OQAM。结果表明,子载波间的噪声通过分块重复和线性组合是相互独立的,而不是相互关联的。在此基础上,可以采用经典的频率相关方法实现信道测量。然后,我们还提出了一种先进的频率相关方法来提高信道测量的精度,该方法假设信道频率响应对于几个连续的子载波是准不变的。通过仿真验证了所提方案的有效性。
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
AI-Empowered Propagation Prediction and Optimization for Reconfigurable Wireless Networks C SVM Classification and KNN Techniques for Cyber Crime Detection A Secure and Efficient Energy Trading Model Using Blockchain for a 5G-Deployed Smart Community Fusion Deep Learning and Machine Learning for Heterogeneous Military Entity Recognition Influence of Embedded Microprocessor Wireless Communication and Computer Vision in Wushu Competition Referees' Decision Support
×
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