Joint Optimization of UAV 3-D Trajectory and Power Allocation in NOMA-Based Emergency Communications

Unmanned aerial vehicle (UAV) is enjoying substantial research attention as a benefit of its compelling flexibility in emergency rescue. However, the energy limitation of UAV is an essential challenge. This paper investigates the joint optimization of the UAV 3D trajectory, user grouping and power allocation in a UAV-assisted emergency network. To enhance the spectral efficiency, the simultaneous utilization of non-orthogonal multiple access (NOMA) is employed. Since the joint optimization of UAV trajectory, user grouping and power allocation results in large-scale solution space, a cluster based particle swarm optimization (CB-PSO) scheme is proposed. Meanwhile, considering the broader impact of iteration and particle diversity, we have developed a novel method for updating the inertia weight with the aim of accelerating convergence. Moreover, the simulated annealing (SA) algorithm is further introduced in the CB-PSO for more performance gain. The simulation results demonstrate that the approach exhibits robust performance while effectively reducing algorithmic complexity.