{"title":"Optimal positioning of flying relays for wireless networks: A LOS map approach","authors":"Junting Chen, D. Gesbert","doi":"10.1109/ICC.2017.7996921","DOIUrl":null,"url":null,"abstract":"This paper considers the exploitation of unmanned aerial vehicles (UAVs) in wireless networking, with which communication-enabled robots operate as flying wireless relays to help fill coverage or capacity gaps in the network. We focus on the particular problem of (automatic) UAV positioning, which is known to crucially affect performance. Existing methods typically rely on statistical models of the air-to-ground channel, and thus, they fail to exploit the fine-grained information of line-of-sight (LOS) conditions at some locations. This paper develops an efficient algorithm to find the best position of the UAV based on the fine-grained LOS information. In spite of the complex terrain topology, the algorithm is able to converge to the optimal UAV position to maximize the end-to-end throughput without a global exploration of a signal strength radio map. Numerical results demonstrate that in a dense urban area, the UAV-aided wireless system with the optimal UAV position can almost double the end-to-end capacity from the base station (BS) to the user as compared to that of a direct BS to user link.","PeriodicalId":6517,"journal":{"name":"2017 IEEE International Conference on Communications (ICC)","volume":"438 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"153","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Communications (ICC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICC.2017.7996921","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 153
Abstract
This paper considers the exploitation of unmanned aerial vehicles (UAVs) in wireless networking, with which communication-enabled robots operate as flying wireless relays to help fill coverage or capacity gaps in the network. We focus on the particular problem of (automatic) UAV positioning, which is known to crucially affect performance. Existing methods typically rely on statistical models of the air-to-ground channel, and thus, they fail to exploit the fine-grained information of line-of-sight (LOS) conditions at some locations. This paper develops an efficient algorithm to find the best position of the UAV based on the fine-grained LOS information. In spite of the complex terrain topology, the algorithm is able to converge to the optimal UAV position to maximize the end-to-end throughput without a global exploration of a signal strength radio map. Numerical results demonstrate that in a dense urban area, the UAV-aided wireless system with the optimal UAV position can almost double the end-to-end capacity from the base station (BS) to the user as compared to that of a direct BS to user link.