Optimization of UAV-assisted Uplink Communication under Energy Constraints

Deep learning has emerged as a powerful tool for addressing the complex challenges in wireless communication systems. This study proposes a novel deep reinforcement learning (DRL)-based approach aimed at maximizing the minimum uplink rate while minimizing the energy consumption of unmanned aerial vehicles (UAVs) in UAV-assisted communication networks over multiple time steps. Simulation results demonstrate the effectiveness and robustness of the proposed approach in jointly optimizing UAV trajectory and bandwidth allocation.