Dynamic deployment of multi‐UAV base stations with deep reinforcement learning

Abstract

Unmanned aerial vehicles (UAVs) can be utilized as aerial base stations (BSs) to provide auxiliary communication services. In this letter, we propose a deep reinforcement learning (DRL)-based dynamic deployment method for multi-UAV communications. The phasic policy gradient (PPG) is designed to improve the sample efficiency and the attention of the multi-UAV deployment. Simulation results are provided to verify the effectiveness of the proposed method.