Abstract:

Aiming at the scenario where unmanned aerial vehicles assist users on the ground to carry out downlink communication, the optimization problem of unmanned aerial vehicle trajectory constraint, power constraint and user access scheduling is established with the objective of maximizing the minimum average reachable rate of users. Considering the coupling of the constraints and the non-convexity of the optimization problem, the constructed optimization problem is modeled as a Markov decision process, and a trajectory planning and power control algorithm of unmanned aerial vehicle-based on deep deterministic policy gradient (DDPG) is proposed. Simulation results show that the proposed algorithm can effectively improve the minimum average achievable rate of users.

Key words: unmanned aerial vehicle, trajectory planning, power control, Markov decision process;deep deterministic policy gradient