Robust Trajectory and Power Control for Cognitive UAV Secrecy Communication

被引:29
|
作者
Gao, Ying [1 ,2 ]
Tang, Hongying [1 ]
Li, Baoqing [1 ]
Yuan, Xiaobing [1 ]
机构
[1] Chinese Acad Sci, Shanghai Inst Microsyst & Informat Technol, Sci & Technol Microsyst Lab, Shanghai 201800, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
来源
IEEE ACCESS | 2020年 / 8卷 / 08期
基金
中国国家自然科学基金;
关键词
Unmanned aerial vehicles; Robustness; Physical layer; Wireless communication; Trajectory optimization; Jamming; UAV communications; cognitive radio; physical layer security; trajectory optimization; robust design; ENABLED SECURE COMMUNICATIONS; VEHICLE BASE STATION; RESOURCE-ALLOCATION; 3-D PLACEMENT; DESIGN; OPTIMIZATION; MAXIMIZATION; DEPLOYMENT; COVERAGE;
D O I
10.1109/ACCESS.2020.2979193
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper investigates the physical layer security issue in an unmanned aerial vehicle (UAV) aided cognitive radio network. Specially, a UAV operates as an aerial secondary transmitter to serve a ground secondary receiver (SR) by sharing the licensed wireless spectrum assigned to primary terrestrial communication networks, and in the meantime multiple eavesdroppers (Eves) try to wiretap the legitimate UAV-to-SR link. Under the assumption that the location formation of the Eves is imperfect, we jointly optimize the robust trajectory and transmit power of the UAV over a finite flight period to maximize the SR's average worst-case secrecy rate, while controlling the co-channel interference imposed on the primary receivers (PRs) below a tolerable level. The design is formulated as a non-convex semi-infinite optimization problem that is challenging to be optimally solved. To deal with it, we first prove that the considered problem can be simplified as a more tractable one, which resolves the location uncertainties of the Eves without the aid of S-Procedure adopted in conventional methods. After that, an efficient iterative algorithm based on successive convex approximation (SCA) is developed to obtain a locally optimal solution. Numerical simulations are provided to demonstrate the effectiveness of our proposed algorithm and offer important system design insights.
引用
收藏
页码:49338 / 49352
页数:15
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