Optimizing Multi-UAV Multi-User System Through Integrated Sensing and Communication for Age of Information (AoI) Analysis

Integrated sensing and communication enhances the spectral efficiency by using shared resources, eliminating the need for separate bandwidth allocations. Unmanned aerial vehicle (UAVs) play a key role in this, offering mobility, flexibility, and extended coverage for serving multiple users, especially in scenarios like disaster response and environmental monitoring. This paper explores multiple UAVs with integrated sensing and communication capabilities, using the Age of Information (AoI) metric to optimize resource allocation for timely data transmission. We propose two algorithms, Variable Particle Swarm Optimization (VPSO) and Twin Variable Neighborhood Particle Swarm Optimization (TVPSO), to jointly optimize power, bandwidth, and UAV trajectories to minimize AoI. Numerical results show the effects of the sensing and communication power ratio, the number of UAVs and the number of users on AoI and energy consumption. Furthermore, TVPSO is shown to outperform other PSO variants and the Deep Q Networks (DQN)-based approach, offering faster convergence and superior performance.