Spectral Efficiency Maximization for UAV-Enabled Integrated Sensing and Communication Systems in Vehicular Networks

Integrated sensing and communications (ISAC) enabled by unmanned aerial vehicles (UAVs) is a promising technology for future vehicular networks. In this paper, we propose a UAV-assisted ISAC scheme designed for vehicular networks. In a static scenario, vehicles are modeled as extended targets with geometric shapes, where multiple resolvable scatterers are uniformly distributed in the vehicle geometry. To address the asymmetric requirements of sensing and communication, a two-stage ISAC scheme is proposed. In the first stage, the UAV sends ISAC signals through wide beams to enhance the sensing accuracy of vehicle position while simultaneously providing communication services. In the second stage, the UAV transmits to a narrow communication-only beam to improve data transmission rates. Our goal is to maximize the spectral efficiency of the communication service by design the UAV flight altitude and time allocation. The resulting optimization problem is formulated as a mixed-integer program, which we solve using a genetic algorithm. Finally, simulation results demonstrate the effectiveness of the proposed algorithm and reveal the tradeoff between communication and sensing.