Optimal UAV deployment in downlink non-orthogonal multiple access system:a two-user case

This paper investigates a unmanned aerial vehicle(UAV)deployment problem in a non-orthogonal multiple access(NOMA)system,where the UAV is deployed as an aerial mobile base station to transmit data to two ground users.An optimization problem is formulated by deploying the UAV for maximizing the sum rate of the two users.In order to solve the optimization problem,the feasible solution region is first reduced to a line segment between two users.Then,the optimization problem is simplified to a univariate problem,which can be solved by derivation under a certain situation,and the corresponding analytical solution is also provided.Moreover,a generalized algorithm,which considers 2 situations,is proposed to further determine the optimal UAV’s location.Specifically,four cases are discussed in the first situation.Extensive simulations are depicted to demonstrate effectiveness of the proposed algorithm and its superiority over the benchmarks in maximizing the two users’sum rate.

Distributed cooperative deployment strategy in multi-UAVs assisted heterogeneous networks

Unmanned aerial vehicle base stations(UAV-BSs)can provide a fast network deployment scheme for heterogeneous networks.However,unmanned aerial vehicle(UAV)has limited capability and cannot assist the base station(BS)well.The ability of a UAV to assist the BSs is limited,and the cluster deployment relies on the leading UAV.The dispersive deployment of multiple UAVs(multi-UAVs)need a macro base station(MBS)to determine their positions to prevent collisions or interference.Therefore,a distributed cooperative deployment scheme is proposed for UAVs to solve this problem.The scheme can increase the ability of UAVs to assist users and reduce the pressure on BSs to deploy UAVs.Firstly,the randomly distributed users are pre-clustered.Then the placement problem was modeled as a circle expansion problem and a pre-clustering radius expansion algorithm was proposed.Under the constraint of users'data rates,it provides services for more users.Finally,the proposed algorithm was compared with the density-aware placement algorithm.The simulation results show that the proposed algorithm can provide services for more users and improve the coverage rate of users while ensuring the data rates.