Optimized Resource Scheduling for UAVs in Cell-Free Massive MIMO Systems with Wireless Power Transfer

Unmanned aerial vehicles (UAVs) are increasingly pivotal as mobile access points in cell-free massive multiple-input multiple-output (CF-mMIMO) systems, supporting both communication and task execution. To extend UAV endurance during complex missions, this paper explores the energy transmission and trajectory design for UAVs utilizing wireless power transfer (WPT) in the CF-mMIMO systems. By optimizing UAV flight trajectory, charging/discharging slots, and beamforming, communication fairness among outage users (UEs) is enhanced while considering the energy consumption constraints imposed by energy replenishment from access points during mission execution. To address this complex problem, we propose an angle search-based communication-assisted deep Q-network (DQN) algorithm, facilitating targeted spatial exploration. Simulation results demonstrate that the proposed approach effectively balances energy efficiency and communication requirements, improving UAV resource utilization and ensuring communication fairness for interrupted UEs, ultimately achieving dynamic regional coverage.