Joint optimization for on-demand deployment of UAVs and spectrum allocation in UAVs-assisted communication

Abstract

To improve the efficiency and fairness of the spectrum allocation for ground communication assisted by unmanned aerial vehicles (UAVs), a joint optimization method for on-demand deployment and spectrum allocation of UAVs is proposed, which is modeled as a mixed-integer non-convex optimization problem (MINCOP). An algorithm to estimate the minimum number of required UAVs is firstly proposed based on the pre-estimation and simulated annealing. The MINCOP is then decomposed into three sub-problems based on the block coordinate descent method, including the spectrum allocation of UAVs, the association between UAVs and ground users, and the deployment of UAVs. Specifically, the optimal spectrum allocation is derived based on the interference mitigation and channel reuse. The association between UAVs and ground users is optimized based on local iterated optimization. A particle-based optimization algorithm is proposed to resolve the subproblem of the UAVs deployment. Simulation results show that the proposed method could effectively improve the minimum transmission rate of UAVs as well as user fairness of spectrum allocation.