Joint Resource Allocation and Trajectory Design for Energy-Efficient UAV Assisted Networks With User Fairness Guarantee

This work explores the utilization of rotary-wing unmanned aerial vehicles (UAV) as aerial base station to provide downlink data services to ground users. The objective is to maximize the energy efficiency (EE) of the UAV assisted communication system while guaranteeing fairness among users. In pursuit of this goal, taking the propulsion power consumption of UAV, the flight constraints of UAV, and the limited communication resources into account, we jointly optimize the power allocation, bandwidth allocation, and trajectory design. Since the corresponding formulated problem is non-convex, to solve it efficiently, we first addressed its non-smoothness and then decompose the problem into two sub-problems: the joint power and bandwidth assignment and the trajectory design sub-problems. We prove that the power allocation and bandwidth assignment sub-problem is quasi-convex fractional optimization. A low-complexity iterative algorithm based on the Dinkelbach's algorithm and the Lagrange duality is proposed to get optimal solution. Successive convex approximation (SCA) together with Dinkelbach's algorithm are adopted to convert the non-convex trajectory optimization problem into convex to get a suboptimal solution for UAV trajectory. Through solving the two sub-problems iteratively by adopting block coordinate descent (BCD) untill convergence, the original problem is solved. Extensive simulation results demonstrate that the proposed algorithm not only has robust convergence properties but also achieves significant improvements in system EE while ensuring user fairness.