Efficient Cooperative Spectrum Sensing in UAV-Assisted Cognitive Wireless Sensor Networks

IF 2.2 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Sensors Letters Pub Date : 2024-09-04 DOI:10.1109/LSENS.2024.3454718
Haoyu Liang;Jun Wu;Tianle Liu;Hao Wang;Weiwei Cao
{"title":"Efficient Cooperative Spectrum Sensing in UAV-Assisted Cognitive Wireless Sensor Networks","authors":"Haoyu Liang;Jun Wu;Tianle Liu;Hao Wang;Weiwei Cao","doi":"10.1109/LSENS.2024.3454718","DOIUrl":null,"url":null,"abstract":"In order to meet the frequency requirements of unmanned aerial vehicles (UAVs), sensors assist UAVs in cooperative spectrum sensing (CSS) to identify available spectrum resources and opportunistically access the channel being underutilized by the primary user (PU). However, in such a UAV-assisted cognitive wireless sensor network (CWSN), the cooperative mode among multiple UAVs with built-in sensors may incur high overhead costs, resulting in the spectrum sensing performance degradation. Therefore, we introduce a differential sequential 1, which incorporates a differential mechanism and leverages the sequential idea based on the classical voting rule to enhance the CSS performance and efficiency. In view of this, we formulate three scenarios to characterize the PU activity and introduce a multislot cooperative mode within a single UAV with built-in sensor to realize cooperative gain. Finally, simulation results demonstrate that the superiority of our proposal with respect to the detection performance and sample size is evident.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Letters","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10666007/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

Abstract

In order to meet the frequency requirements of unmanned aerial vehicles (UAVs), sensors assist UAVs in cooperative spectrum sensing (CSS) to identify available spectrum resources and opportunistically access the channel being underutilized by the primary user (PU). However, in such a UAV-assisted cognitive wireless sensor network (CWSN), the cooperative mode among multiple UAVs with built-in sensors may incur high overhead costs, resulting in the spectrum sensing performance degradation. Therefore, we introduce a differential sequential 1, which incorporates a differential mechanism and leverages the sequential idea based on the classical voting rule to enhance the CSS performance and efficiency. In view of this, we formulate three scenarios to characterize the PU activity and introduce a multislot cooperative mode within a single UAV with built-in sensor to realize cooperative gain. Finally, simulation results demonstrate that the superiority of our proposal with respect to the detection performance and sample size is evident.
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
无人机辅助认知无线传感器网络中的高效合作频谱感知
为了满足无人飞行器(UAV)的频率要求,传感器协助无人飞行器进行合作频谱感知(CSS),以识别可用频谱资源,并伺机访问主用户(PU)未充分利用的信道。然而,在这种无人机辅助认知无线传感器网络(CWSN)中,多个内置传感器的无人机之间的合作模式可能会产生高昂的开销成本,导致频谱感知性能下降。因此,我们引入了一种差分序列 1,它结合了差分机制,并利用基于经典投票规则的序列思想来提高 CSS 性能和效率。有鉴于此,我们制定了三种场景来描述 PU 活动,并在单个内置传感器的无人机内引入多频段合作模式,以实现合作增益。最后,仿真结果表明,我们的建议在检测性能和样本量方面具有明显的优势。
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
IEEE Sensors Letters
IEEE Sensors Letters Engineering-Electrical and Electronic Engineering
CiteScore
3.50
自引率
7.10%
发文量
194
期刊最新文献
An Efficient and Scalable Internet of Things Framework for Smart Farming Machine Learning-Based Low-Cost Colorimetric Sensor for pH and Free-Chlorine Measurement A Portable and Flexible On-Road Sensing System for Traffic Monitoring Advancing General Sensor Data Synthesis by Integrating LLMs and Domain-Specific Generative Models $\mu$WSense: A Self-Sustainable Microwave-Powered Battery-Less Wireless Sensor Node for Temperature and Humidity Monitoring
×
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