DDPG-based UAV Trajectory Design for Fair and Energy Efficient Communication

Unmanned aerial vehicles (UAVs) are employed in rural areas to improve network connectivity and ensure communication during disasters. Serving as airborne base stations (BSs) or relays, they extend coverage. However, UAVs face challenges like limited energy and transmission capability, which restrict their range and ability to maintain connectivity over time. In this paper, we propose a deep deterministic policy gradient (DDPG)-based trajectory design of UAVs to optimize both energy efficiency and fair communication. Our proposed DDPG-based method refines UAV trajectories based on predefined factors such as communication throughput, energy consumption, fairness, and connectivity. The simulation outcomes demonstrate that our proposed DDPG-based algorithm consistently outperforms by up to 65% compared to competitive approaches in terms of energy efficiency and communication fairness.