Secure Transmission Design for Aerial IRS Assisted Wireless Networks

• Published in: IEEE transactions on communications Vol. 71; no. 6; pp. 3528 - 3540
• Main Authors: Wei, Wenjing, Pang, Xiaowei, Tang, Jie, Zhao, Nan, Wang, Xianbin, Nallanathan, Arumugam
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Antenna arrays; Antennas; Array signal processing; Artificial intelligence; Autonomous aerial vehicles; Beamforming; Communication system security; Eavesdropping; Hovering; Intelligent reflecting surface; joint beamforming optimization; Line of sight; Optimization; physical layer security; Reconfiguration; Secrecy aspects; Security; unmanned aerial vehicle; Unmanned aerial vehicles; Wireless networks
• ISSN: 0090-6778; 1558-0857
• DOI: 10.1109/TCOMM.2023.3257387

Combining intelligent reflecting surface (IRS) and unmanned aerial vehicle (UAV) offers a new degree of freedom to improve the coverage performance. However, it is more challenging to secure the air-ground transmission, due to the line-of-sight (LoS) links established by UAV. Since IRS is a promising solution for wireless environment reconfiguration, in this paper, we propose an aerial IRS-assisted secure transmission design in wireless networks. In particular, an access point (AP) equipped with a uniform planar array serves several single-antenna legitimate users in the presence of multiple single-antenna eavesdroppers, whose precise positions are unknown. An IRS is mounted on the UAV to help establish desired virtual LoS links between the AP and legitimate users, while ensuring their security. We aim to maximize the worst-case sum secrecy rate by jointly optimizing the hovering position of UAV, the transmit beamforming of AP and the phase shifts of IRS, subject to the requirement of minimum rate for legitimate users. To tackle this non-convex problem, we first decompose it into three subproblems, which are transformed into convex ones via successive convex approximation. An alternating algorithm is then proposed to solve them iteratively. Simulation results show the effectiveness of the proposed scheme and the security improvement by the joint optimization.