  Unmanned aerial vehicle (UAV)-enabled wireless powered communication networks
(WPCNs) are promising technologies in 5G/6G wireless communications, while
there are several challenges about UAV power allocation and scheduling to
enhance the energy utilization efficiency, considering the existence of
obstacles. In this work, we consider a UAV-enabled WPCN scenario that a UAV
needs to cover the ground wireless devices (WDs). During the coverage process,
the UAV needs to collect data from the WDs and charge them simultaneously. To
this end, we formulate a joint-UAV power and three-dimensional (3D) trajectory
optimization problem (JUPTTOP) to simultaneously increase the total number of
the covered WDs, increase the time efficiency, and reduce the total flying
distance of UAV so as to improve the energy utilization efficiency in the
network. Due to the difficulties and complexities, we decompose it into two sub
optimization problems, which are the UAV power allocation optimization problem
(UPAOP) and UAV 3D trajectory optimization problem (UTTOP), respectively. Then,
we propose an improved non-dominated sorting genetic algorithm-II with K-means
initialization operator and Variable dimension mechanism (NSGA-II-KV) for
solving the UPAOP. For UTTOP, we first introduce a pretreatment method, and
then use an improved particle swarm optimization with Normal distribution
initialization, Genetic mechanism, Differential mechanism and Pursuit operator
(PSO-NGDP) to deal with this sub optimization problem. Simulation results
verify the effectiveness of the proposed strategies under different scales and
settings of the networks.
