{"title":"针对协同窃听者的物理层安全通信无人机轨迹优化","authors":"Huanran Zhang, Lingfeng Shen, Ning Wang, X. Mu","doi":"10.1109/CyberC55534.2022.00055","DOIUrl":null,"url":null,"abstract":"In this paper, we study the maximization of the secrecy throughput of an air-to-ground UAV communication system through UAV trajectory optimization, in a scenario where multiple cooperating eavesdroppers exist. Two cooperative eavesdropping strategies, namely Selection Combing-Cooperative Eavesdropping (SC-CE) and Maximal Ratio Combining-Cooperative Eavesdropping (MRC-CE) are considered for the cooperating eavesdroppers. Based on the mathematical forms of the formulated optimization problems corresponding to the two cooperative eavesdropping schemes, we propose to use the Trajectory Increment Iteration (TII) algorithm and the Particle Swarm Optimization (PSO) algorithm to solve for the optimal trajectory, respectively. Simulation results show that by optimizing the UAV trajectory against cooperative eavesdropping, the physical layer security performance of the system can be effectively improved.","PeriodicalId":234632,"journal":{"name":"2022 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"UAV Trajectory Optimization for PHY Secure Communication Against Cooperative Eavesdroppers\",\"authors\":\"Huanran Zhang, Lingfeng Shen, Ning Wang, X. Mu\",\"doi\":\"10.1109/CyberC55534.2022.00055\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we study the maximization of the secrecy throughput of an air-to-ground UAV communication system through UAV trajectory optimization, in a scenario where multiple cooperating eavesdroppers exist. Two cooperative eavesdropping strategies, namely Selection Combing-Cooperative Eavesdropping (SC-CE) and Maximal Ratio Combining-Cooperative Eavesdropping (MRC-CE) are considered for the cooperating eavesdroppers. Based on the mathematical forms of the formulated optimization problems corresponding to the two cooperative eavesdropping schemes, we propose to use the Trajectory Increment Iteration (TII) algorithm and the Particle Swarm Optimization (PSO) algorithm to solve for the optimal trajectory, respectively. Simulation results show that by optimizing the UAV trajectory against cooperative eavesdropping, the physical layer security performance of the system can be effectively improved.\",\"PeriodicalId\":234632,\"journal\":{\"name\":\"2022 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CyberC55534.2022.00055\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CyberC55534.2022.00055","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
UAV Trajectory Optimization for PHY Secure Communication Against Cooperative Eavesdroppers
In this paper, we study the maximization of the secrecy throughput of an air-to-ground UAV communication system through UAV trajectory optimization, in a scenario where multiple cooperating eavesdroppers exist. Two cooperative eavesdropping strategies, namely Selection Combing-Cooperative Eavesdropping (SC-CE) and Maximal Ratio Combining-Cooperative Eavesdropping (MRC-CE) are considered for the cooperating eavesdroppers. Based on the mathematical forms of the formulated optimization problems corresponding to the two cooperative eavesdropping schemes, we propose to use the Trajectory Increment Iteration (TII) algorithm and the Particle Swarm Optimization (PSO) algorithm to solve for the optimal trajectory, respectively. Simulation results show that by optimizing the UAV trajectory against cooperative eavesdropping, the physical layer security performance of the system can be effectively improved.