Optimization Of UAV Base Stations Under Backhaul And User Quality-of-Service Constraints

In wireless communication systems,unmanned aerial vehicles(UAVs)can be used as aerial base stations to assist ground base stations for network coverage.If the trajectory and communication resource of a UAV base station can be optimized according to the actual situation during the communication process,the throughput of the whole system can be improved.The UAV base station system studied in this thesis will take into account the constraints of the backhaul link and user quality of service.This is because when the bandwidth of the backhaul link is limited,it may limit the overall performance of the UAV base station communication,and in a wireless communication network,the users may have different quality of service requirements generally.What’s more,the mobility of a UAV base station has a considerable impact on the optimization of overall network performance.Combining trajectory optimization and power control,a UAV base station can provide service for ground users by establishing stable line-of-sight links,and can also avoid interference to unintended users.In order to further improve the communication performance,the system can also adjust the bandwidth of each data link adaptively according to the channel state.Therefore,this thesis studies allocating communication resource and optimizing the trajectory of UAV base stations according to the changing dynamic of the UAV communication networks to make full use of all optimization degrees of freedom to improve the communication performance of the system.The main contents of this thesis are as follows.First,a method for optimizing the bandwidth,power,and trajectory of a UAV base station system with the constraints on the backhaul link and the users’ quality of service has been proposed,where the ground base station(backhaul link gateway)sends information to the UAV,and the UAV acting as an aerial base station forwards the information to the ground users.Due to the spectrum scarcity of the network,the backhaul link which connecting the backhaul gateway and the UAV base station shares the same spectrum with the data links which connecting the UAV base station and the users.In order to improve the rate performance of the delay-tolerant users and to guarantee the quality of service of the delay-sensitive users,this thesis optimizes the bandwidth of the backhaul link and data link,the transmission power allocated to the different users and the trajectory of the UAV base station to maximize the minimum rate of delay-tolerance users,subject to the constraints on the mobility of the UAV,the total bandwidth,the total transmit power,the rate of backhaul data,and the minimum rate requirements of the delay-sensitive users.Although the formulated problem is non-convex and difficult to find the optimal solution,we propose an efficient algorithm to find a suboptimal solution to it by using the alternating optimization and successive convex optimization methods.Simulation results show that the proposed joint optimization algorithm achieves significantly higher minimum user rate than the benchmark schemes.Then,a method for optimizing the bandwidth,power and flight path of a multi-UAV base station system with the backhaul constraint has been studied,where multiple UAVs acting as aerial base stations receive information from the backhaul link gateway and forward it to their corresponding user groups(each UAV base station serves a group of users).In order to improve the communication performance of the users and use spectrum resource reasonably and efficiently,this thesis maximize the minimum rate of all ground users by jointly optimizing the bandwidth and the transmit power of the overall data link,the trajectories of the UAV base stations.This joint optimization is subject to the constraints of the backhaul link,the total bandwidth,the total transmit power,and the UAVs’ mobility and anti-collision requirement.Although the formulated problem is non-convex and difficult to find the optimal solution,we propose an efficient algorithm to find a suboptimal solution to it by using the alternating optimization and successive convex optimization methods.Simulation results show that the proposed joint optimization algorithm has significantly higher minimum user rate than the benchmark schemes.