Securing Transmission for UAV Swarm-Enabled Communication Network

• Published in: IEEE systems journal Vol. 16; no. 4; pp. 5200 - 5211
• Main Authors: Dong, Runze, Wang, Buhong, Cao, Kunrui, Cheng, Tianhao
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Antenna arrays; Array signal processing; Artificial noise (AN); Base stations; Beamforming; block coordinate descent; Communication; Communication networks; Communications networks; Eavesdropping; Fixed wings; Line of sight communication; Optimization; physical layer security; Relays; Trajectory; trajectory optimization; unmanned aerial vehicle (UAV) swarm; Unmanned aerial vehicles
• ISSN: 1932-8184; 1937-9234
• DOI: 10.1109/JSYST.2021.3111746

Deploying unmanned aerial vehicles (UAVs) in communication networks could achieve desirable degrees of freedom, but resulting from the high line-of-sight link attributes, security threats faced by UAV communications are serious. Taking that into consideration, we focus on a UAV swarm-enabled communication network in this article, where a fixed-wing UAV acts as a legitimate user and a neighboring UAV eavesdropper attempts to eavesdrop the confidential information forwarded by rotary-wing UAV relays. In particular, we jointly optimize transmit power on the base station and UAV relays, power allocation coefficient and beamforming on UAV relays, and trajectory of the fixed-wing UAV to maximize the average secrecy rate. Due to the nonconvexity of the optimization problem, the block coordinate descent method is utilized to solve it. Specifically, the overall optimizing problem is divided into four subproblems in which the transmit power, power allocation coefficient, beamforming vector, and the trajectory of user are optimized, respectively. By employing the successive convex approximate method, subproblems are transformed to convex problems which are numerically tractable. Numerical simulations validate the effectiveness of the proposed algorithm and show that compared with benchmark schemes, the considered transmission scheme with artificial noise and optimized network parameters can improve secrecy rate by about 13.8%.