Wideband spectrum sensing using low-power IoT device

Hyeongyun Kim, Junil Ahn, Haewoon Nam
{"title":"Wideband spectrum sensing using low-power IoT device","authors":"Hyeongyun Kim, Junil Ahn, Haewoon Nam","doi":"10.1109/ICTC49870.2020.9289566","DOIUrl":null,"url":null,"abstract":"We consider a compressive wideband spectrum sensing for low-power IoT devices as secondary users(SUs). We present the proposed scheme for cost-effective compressive sensing for wideband spectrum sensing with a large number of distributed SUs. SUs have a single RF-chain for the compressive sensing and the measurement samples obtained at each SU are sent to the fusion center. The fusion center performs the proposed algorithm which estimates the minimum measurement samples for the reconstruction process. Among the total measurement samples by SUs, the rest of the samples except for the minimum number of samples are used for cooperative spectrum sensing. The original signal vector with the minimum measurement samples is reconstructed and cooperative gain is obtained by using the remainder of measurement samples effectively. We compare the performance of the proposed algorithm with the conventional compressive sensing scheme and the result shows that the proposed algorithm has better performance specially at the high sparsity order region.","PeriodicalId":282243,"journal":{"name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"2007 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTC49870.2020.9289566","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

We consider a compressive wideband spectrum sensing for low-power IoT devices as secondary users(SUs). We present the proposed scheme for cost-effective compressive sensing for wideband spectrum sensing with a large number of distributed SUs. SUs have a single RF-chain for the compressive sensing and the measurement samples obtained at each SU are sent to the fusion center. The fusion center performs the proposed algorithm which estimates the minimum measurement samples for the reconstruction process. Among the total measurement samples by SUs, the rest of the samples except for the minimum number of samples are used for cooperative spectrum sensing. The original signal vector with the minimum measurement samples is reconstructed and cooperative gain is obtained by using the remainder of measurement samples effectively. We compare the performance of the proposed algorithm with the conventional compressive sensing scheme and the result shows that the proposed algorithm has better performance specially at the high sparsity order region.
使用低功耗物联网设备的宽带频谱传感
我们考虑将压缩宽带频谱感知用于低功耗物联网设备作为辅助用户(su)。我们提出了一种具有成本效益的压缩感知方案,用于具有大量分布式单元的宽带频谱感知。单个单元有一条用于压缩感知的射频链,在每个单元获得的测量样本被发送到融合中心。融合中心执行所提出的算法,估计用于重建过程的最小测量样本。在SUs的总测量样本中,除最小样本数外,其余样本用于协同频谱感知。利用最小测量样本重构原始信号矢量,有效利用剩余测量样本获得协同增益。将该算法与传统压缩感知算法的性能进行了比较,结果表明,该算法在高稀疏阶域具有更好的性能。
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:604180095
Book学术官方微信