Xinran Fang, Yanmin Wang, W. Feng, Yunfei Chen, B. Ai
{"title":"Power Allocation for Maritime Cognitive Satellite-UAV-Terrestrial Networks","authors":"Xinran Fang, Yanmin Wang, W. Feng, Yunfei Chen, B. Ai","doi":"10.1109/ICCICC50026.2020.9450217","DOIUrl":null,"url":null,"abstract":"In this paper, we investigate hybrid satellite-unmanned aerial vehicle (UAV)-terrestrial networks for maritime coverage enhancement. We adopt tethered UAVs to provide aerial base station (BS) sites, and orchestrate onshore and UAV-mounted BSs in a user-centric manner. To address the spectrum scarcity problem, all available spectrum is shared among satellites, UAVs and terrestrial base stations (TBSs). This generates undesirable challenging co-channel interference (CCI) under the irregular cell-free system topology. We establish a cognitive framework to sense not only the spectrum status but also ships’ position information. According to the cognitive information, user-centric virtual clusters are self organized by a group of UAVs and onshore BSs. Besides, location-dependent large-scale channel state information (CSI) can be obtained through the cognitive position information. We thus optimize the power allocation strategy with only the large-scale CSI, to further mitigate both the inter-cluster interference and leakage interference to satellite users. The problem is non-convex. By using the random matrix theory and successive convex optimization methods, we solve it in an iterative way. Simulation results corroborate the efficiency of the proposed cognitive framework and the presented power allocation scheme.","PeriodicalId":212248,"journal":{"name":"2020 IEEE 19th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"541 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 19th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCICC50026.2020.9450217","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In this paper, we investigate hybrid satellite-unmanned aerial vehicle (UAV)-terrestrial networks for maritime coverage enhancement. We adopt tethered UAVs to provide aerial base station (BS) sites, and orchestrate onshore and UAV-mounted BSs in a user-centric manner. To address the spectrum scarcity problem, all available spectrum is shared among satellites, UAVs and terrestrial base stations (TBSs). This generates undesirable challenging co-channel interference (CCI) under the irregular cell-free system topology. We establish a cognitive framework to sense not only the spectrum status but also ships’ position information. According to the cognitive information, user-centric virtual clusters are self organized by a group of UAVs and onshore BSs. Besides, location-dependent large-scale channel state information (CSI) can be obtained through the cognitive position information. We thus optimize the power allocation strategy with only the large-scale CSI, to further mitigate both the inter-cluster interference and leakage interference to satellite users. The problem is non-convex. By using the random matrix theory and successive convex optimization methods, we solve it in an iterative way. Simulation results corroborate the efficiency of the proposed cognitive framework and the presented power allocation scheme.