Efficient white space boundary estimation with heterogeneous types of sensors

I. Kanno, K. Horihata, Akio Hasegawa, T. Maeyama, Y. Takeuchi
{"title":"Efficient white space boundary estimation with heterogeneous types of sensors","authors":"I. Kanno, K. Horihata, Akio Hasegawa, T. Maeyama, Y. Takeuchi","doi":"10.1109/ISANP.2014.7026583","DOIUrl":null,"url":null,"abstract":"This paper proposes a novel framework for white space (WS) boundary estimation which utilizes heterogeneous types of sensors. The proposed framework utilizes sensors not for spectrum sensing, but for estimating the propagation parameters that characterize the boundary to the incumbent radio systems (IRSs) to identify WS efficiently. The position of IRS emitter (transmission source), its transmission power, and pathloss around it are estimated to identify the boundary from collected sensing data. The former 2 parameters and latter one are estimated with sparsely deployed long-range sensors and densely deployed low-end small sensors, respectively. In addition, its result of preliminary feasibility study is described.","PeriodicalId":354277,"journal":{"name":"2014 International Symposium on Antennas and Propagation Conference Proceedings","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Symposium on Antennas and Propagation Conference Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISANP.2014.7026583","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

This paper proposes a novel framework for white space (WS) boundary estimation which utilizes heterogeneous types of sensors. The proposed framework utilizes sensors not for spectrum sensing, but for estimating the propagation parameters that characterize the boundary to the incumbent radio systems (IRSs) to identify WS efficiently. The position of IRS emitter (transmission source), its transmission power, and pathloss around it are estimated to identify the boundary from collected sensing data. The former 2 parameters and latter one are estimated with sparsely deployed long-range sensors and densely deployed low-end small sensors, respectively. In addition, its result of preliminary feasibility study is described.
基于异构类型传感器的高效空白边界估计
本文提出了一种利用异构类型传感器进行空白边界估计的新框架。提出的框架利用传感器不是用于频谱感知,而是用于估计现有无线电系统(IRSs)边界特征的传播参数,以有效地识别WS。通过估算IRS发射极(发射源)的位置、发射功率和周围的路径损耗,从采集到的传感数据中识别出边界。前2个参数和后2个参数分别用稀疏部署的远程传感器和密集部署的低端小型传感器估计。并对其初步可行性研究结果进行了描述。
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