{"title":"基于sir测量PSO算法的无人机三维定位","authors":"Wentao Liu, Guanchong Niu, Qi Cao, Man-On Pun, Junting Chen","doi":"10.1109/GCWkshps45667.2019.9024696","DOIUrl":null,"url":null,"abstract":"This work studies the deployment of unmanned aerial vehicles (UAVs) as emergency access points to provide wireless services to users in a green field. Specifically, three fundamental design issues are explored under practical 3D air-to-ground (ATG) channel models, namely the minimum number of UAVs, their optimal deployment locations and the optimal transmit power allocation. To decouple these design goals, a particle swarm optimization (PSO)-based scheme in conjunction with the balanced Signal to Interference plus Noise Ratio (SINR) transmit power allocation is proposed. Exploiting the closed-form expressions of the SINR-balanced optimal power allocation and the resulting SINR, the proposed PSO-based scheme optimizes the UAV location generation by generation. Furthermore, a K-means clustering-based initialization scheme is developed to improve the performance of the proposed PSO-based scheme. Finally, a power fine-tuning scheme is devised to further reduce the total transmit power. Extensive simulation is performed to confirm the good performance of the proposed scheme.","PeriodicalId":210825,"journal":{"name":"2019 IEEE Globecom Workshops (GC Wkshps)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"3-D Placement of UAVs Based on SIR-Measured PSO Algorithm\",\"authors\":\"Wentao Liu, Guanchong Niu, Qi Cao, Man-On Pun, Junting Chen\",\"doi\":\"10.1109/GCWkshps45667.2019.9024696\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work studies the deployment of unmanned aerial vehicles (UAVs) as emergency access points to provide wireless services to users in a green field. Specifically, three fundamental design issues are explored under practical 3D air-to-ground (ATG) channel models, namely the minimum number of UAVs, their optimal deployment locations and the optimal transmit power allocation. To decouple these design goals, a particle swarm optimization (PSO)-based scheme in conjunction with the balanced Signal to Interference plus Noise Ratio (SINR) transmit power allocation is proposed. Exploiting the closed-form expressions of the SINR-balanced optimal power allocation and the resulting SINR, the proposed PSO-based scheme optimizes the UAV location generation by generation. Furthermore, a K-means clustering-based initialization scheme is developed to improve the performance of the proposed PSO-based scheme. Finally, a power fine-tuning scheme is devised to further reduce the total transmit power. Extensive simulation is performed to confirm the good performance of the proposed scheme.\",\"PeriodicalId\":210825,\"journal\":{\"name\":\"2019 IEEE Globecom Workshops (GC Wkshps)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE Globecom Workshops (GC Wkshps)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GCWkshps45667.2019.9024696\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Globecom Workshops (GC Wkshps)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GCWkshps45667.2019.9024696","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
3-D Placement of UAVs Based on SIR-Measured PSO Algorithm
This work studies the deployment of unmanned aerial vehicles (UAVs) as emergency access points to provide wireless services to users in a green field. Specifically, three fundamental design issues are explored under practical 3D air-to-ground (ATG) channel models, namely the minimum number of UAVs, their optimal deployment locations and the optimal transmit power allocation. To decouple these design goals, a particle swarm optimization (PSO)-based scheme in conjunction with the balanced Signal to Interference plus Noise Ratio (SINR) transmit power allocation is proposed. Exploiting the closed-form expressions of the SINR-balanced optimal power allocation and the resulting SINR, the proposed PSO-based scheme optimizes the UAV location generation by generation. Furthermore, a K-means clustering-based initialization scheme is developed to improve the performance of the proposed PSO-based scheme. Finally, a power fine-tuning scheme is devised to further reduce the total transmit power. Extensive simulation is performed to confirm the good performance of the proposed scheme.