Secrecy Rate Maximization via Joint Robust Beamforming and Trajectory Optimization for Mobile User in ISAC-UAV System

• Published in: Drones (Basel) Vol. 9; no. 8; p. 536
• Main Authors: Xu, Lvxin, Zhang, Zhi, Yin, Liuguo
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.08.2025
• Subjects: Accuracy; Algorithms; Approximation; Beamforming; Communication; Constraints; Data security; Design; Drone aircraft; Energy efficiency; Integrated approach; integrated sensing and communication; Investigations; Line of sight communication; Localization; Mathematical optimization; Methods; Optimization algorithms; robust beamforming; Robustness; secrecy sum-rate; Signal processing; Trajectory optimization; trajectory planning; unmanned aerial vehicle; Unmanned aerial vehicles; China
• ISSN: 2504-446X; 2504-446X
• DOI: 10.3390/drones9080536

Unmanned aerial vehicles (UAVs) have emerged as a promising platform for integrated sensing and communication (ISAC) due to their mobility and deployment flexibility. By adaptively adjusting their flight trajectories, UAVs can maintain favorable line-of-sight (LoS) communication links and sensing angles, thus enhancing overall system performance in dynamic and complex environments. However, ensuring physical layer security (PLS) in such UAV-assisted ISAC systems remains a significant challenge, particularly in the presence of mobile users and potential eavesdroppers. This manuscript proposes a joint optimization framework that simultaneously designs robust transmit beamforming and UAV trajectories to secure downlink communication for multiple ground users. At each time slot, the UAV predicts user positions and maximizes the secrecy sum-rate, subject to constraints on total transmit power, multi-target sensing quality, and UAV mobility. To tackle this non-convex problem, we develop an efficient optimization algorithm based on successive convex approximation (SCA) and constrained optimization by linear approximations (COBYLA). Numerical simulations validate that the proposed framework effectively enhances the secrecy performance while maintaining high-quality sensing, achieving near-optimal performance under realistic system constraints.