Secure Beamforming Design for UAV-Empowered Integrated Sensing and Communication

Abstract

Integrated sensing and communication (ISAC) systems assisted by unmanned aerial vehicles (UAVs) are susceptible to eavesdropping, making secure information transmission a critical area of research. We propose a joint optimization algorithm to improve the security of UAV-assisted ISAC systems through coordinated adjustments of transmit beamforming and UAV position. The optimization problem aims to minimize the maximum eavesdropping signal-to-interference-plus-noise ratio (SINR) across multiple legitimate users while adhering to three distinct constraints: service quality for legitimate users, sensing requirements for detecting eavesdroppers, and limitations on system transmit power. To address the non-convex optimization challenge effectively, the problem is decomposed into sub-problems focusing on the optimization of transmit beamforming and UAV position. These sub-problems are solved using semidefinite relaxation (SDR), the Dinkelbach method, and successive convex approximation (SCA), with iterative alternation achieving optimal values for the transmit beamforming and UAV position while also proving the convergence of the algorithm. Lastly, simulation results illustrate that the proposed algorithm markedly improves the system’s security performance while preserving its communication and sensing capabilities.