Intelligent Reflecting Surface and UAV Assisted Secrecy Communication in Millimeter-Wave Networks

Abstract

In this paper, we consider the secure transmission problem in an unmanned aerial vehicle (UAV) and intelligent reflecting surface (IRS) assisted mmWave networks in the presence of an eavesdropper. The UAV base station (UAV-BS) and IRS are deployed to overcome the blockages. Artificial noise (AN) is exploited against the eavesdropper. Aiming to maximize the secrecy rate, we jointly design the positions and beamforming of UAV-BS and IRS, where the positions here represent the deployed position of the UAV-BS and the activation position of the IRS. Meanwhile, the maximum transmits power, minimum height constraint for UAV-BS, and the legitimate receiver minimum rate constraint are required. To obtain the optimal UAV-BS position, the elevation angle-dependent probabilistic LoS air-to-ground channel is exploited in this network. To tackle the formulated non-convex problem, we divide it into two subproblems: (1) design UAV-BS and IRS positions; (2) design UAV-BS and IRS beamforming. Moreover, to reduce the complexity, we propose an ideal beamforming model to find the near-optimal positions of UAV-BS and IRS. Then, semidefinite relaxation (SDR) is utilized to cope with the highly coupled and high-dimensional variable vectors. Finally, we obtain a sub-optimal solution by an efficient and low-complexity alternating optimization algorithm. Numerical results demonstrate the improvement of secrecy rate by jointly designing the positions as well as the significant performance gains achieved by our proposed schemes over benchmark schemes.