Harris K. Armeniakos, Petros S. Bithas, Konstantinos Maliatsos, Athanasios G. Kanatas
{"title":"Joint Energy and SINR Coverage Probability in UAV Corridor-assisted RF-powered IoT Networks","authors":"Harris K. Armeniakos, Petros S. Bithas, Konstantinos Maliatsos, Athanasios G. Kanatas","doi":"arxiv-2409.07333","DOIUrl":null,"url":null,"abstract":"This letter studies the joint energy and signal-to-interference-plus-noise\n(SINR)-based coverage probability in Unmanned Aerial Vehicle (UAV)-assisted\nradio frequency (RF)-powered Internet of Things (IoT) networks. The UAVs are\nspatially distributed in an aerial corridor that is modeled as a\none-dimensional (1D) binomial point process (BPP). By accurately capturing the\nline-of-sight (LoS) probability of a UAV through large-scale fading i) an exact\nform expression for the energy coverage probability is derived, and ii) a tight\napproximation for the overall coverage performance is obtained. Among several\nkey findings, numerical results reveal the optimal number of deployed UAV-BSs\nthat maximizes the joint coverage probability, as well as the optimal length of\nthe UAV corridors when designing such UAV-assisted IoT networks.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - EE - Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.07333","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
This letter studies the joint energy and signal-to-interference-plus-noise
(SINR)-based coverage probability in Unmanned Aerial Vehicle (UAV)-assisted
radio frequency (RF)-powered Internet of Things (IoT) networks. The UAVs are
spatially distributed in an aerial corridor that is modeled as a
one-dimensional (1D) binomial point process (BPP). By accurately capturing the
line-of-sight (LoS) probability of a UAV through large-scale fading i) an exact
form expression for the energy coverage probability is derived, and ii) a tight
approximation for the overall coverage performance is obtained. Among several
key findings, numerical results reveal the optimal number of deployed UAV-BSs
that maximizes the joint coverage probability, as well as the optimal length of
the UAV corridors when designing such UAV-assisted IoT networks.