Robust Secure Transmission for IRS-Assisted UAV-ISAC Networks without Eavesdropping CSI

Integrated sensing and communication (ISAC), is emerging as a promising technology for future mobile networks. This paper studies the robust secure transmission for intelligent reflecting surface (IRS) assisted unmanned aerial vehicle (UAV)-ISAC networks without eavesdropping channel state information. Particularly, the UAV, as a dual-functional ISAC base station, serves $K$ communication users and senses $J$ targets with an IRS. Furthermore, an eavesdropper aims at eavesdropping the private information from the UAV to $K$ users. Without eavesdropping channel state information, a secure transmission scheme is proposed to maximize the average achievable rate via jointly designing the transmit power allocation, the scheduling of users and targets, the phase shifts at IRS, and the trajectory and velocity of the UAV. Owing to the non-convexity, an iterative algorithm based on the alternating optimization, the successive convex approximation and the manifold optimization is proposed to obtain a sub-optimal solution. Simulation results verify the effectiveness of the proposed scheme.