Secure and Energy-Efficient Communication Design in Low-Altitude Intelligent Vehicular Networks via Joint Power and Trajectory Optimization

The integration of uncrewed aerial vehicles (UAVs) into vehicular networks (VNets) holds great potential for extending communication coverage and enhancing network capacity. However, the high mobility of UAVs and intelligent connected vehicles (ICVs) leads to fast time-varying channels, while ensuring communication security and energy efficiency in such dynamic environments remains a challenging task. To address these issues, this paper aims to jointly maximize the sum secrecy rate of low-altitude intelligent VNets and minimize the total energy consumption of the UAV. Given the NP-hard nature of the formulated problem, we decompose it into three subproblems: UAV trajectory optimization, base station (BS) transmitted power control, and UAV transmitted power allocation. An alternating optimization (AO) framework is developed to solve them iteratively, leveraging the Newton method, model predictive control, and the shooting method, respectively. We further provide a theoretical analysis of the computational complexity and convergence property of the proposed AO framework. Simulation results demonstrate that our scheme outperforms state-of-the-art schemes in terms of sum secrecy rate and energy efficiency under various network conditions.