Research On UAV Base Station Deployment And Resource Allocation Strategy

Unmanned aerial vehicles(UAVs)have their own characteristics of flexibility,on-demand deployment and economy,coupled with the cost reduction of UAVs and the miniaturization of communication and computing equipment,making UAV base stations in beyond the fifth generation mobile communication(B5G)and the sixth generation mobile communication(6G)technology has received great attention.Compared with traditional ground base stations,deployment location is an important optimization dimension unique to UAV base stations.The deployment location of the UAV base station has a direct impact on the performance of the channel quality,network throughput,and energy efficiency of the UAV base station.At present,research on UAV base stations mainly focuses on the joint optimization of deployment location and resource allocation of UAV base stations to improve network performance.However,there is a problem that the air-ground channel model used between the UAV base station and the ground user is inaccurate,and the capacity of the air-ground channel cannot be truly represented.Different air-ground channel models are used,which will lead to completely different UAV deployment and resource allocation strategies when optimizing network performance.In view of the above problems,this paper is based on the real urban statistical air-ground probability line-of-sight(LoS)channel model,and improves network throughput and UAV energy by studying UAV base station deployment and resource allocation strategies.In addition,in a scenario assisted by a reconfigurable intelligent surface(RIS),this paper designs an algorithm to optimize the deployment of UAV base stations,bandwidth and power allocation,and passive beamforming of RIS to achieve fair service for UAV base stations.The main research contents and innovations of this paper are as follows:Aiming at the problem that the location of the UAV base station affects the LoS channel probability of the air-ground link and the timevarying characteristics of the wireless channel,a UAV base station deployment and resource allocation strategy to ensure the quality of service(QoS)is proposed to improve the network throughput.An emergency communication scenario in which a UAV base station serves multiple ground users with statistical QoS requirements on the downlink is considered.Constrained by the statistical QoS of all ground users,an optimization problem that maximizes all ground users and effective capacity is formulated by jointly optimizing the three-dimensional(3D)location,bandwidth,and power of UAV base stations.The formulated optimization problem is a non-convex optimization problem.In this paper,an iterative algorithm based on block coordinate descent and continuous convex optimization techniques is proposed to solve this non-convex optimization problem.Finally,extensive numerical simulations are carried out to show that the proposed algorithm has fast convergence.characteristics,and the obtained maximum and effective capacity are also significantly better than the benchmark comparison experiments.Aiming at the energy limitation of UAV base stations,an energyefficient UAV base station deployment and resource allocation strategy is proposed to improve energy efficiency and extend service time.This research point is an extension of the previous research content.First,the energy efficiency is defined as the ratio of the sum effective capacity of all ground users to the energy consumed by the UAV.Among them,the energy consumption of the UAV is divided into three parts:communication energy consumption,circuit energy consumption and hovering energy consumption.An optimization problem to maximize energy efficiency is framed,under the premise of satisfying the statistical QoS of all ground users,by optimizing the height,bandwidth and power allocation of the UAV base station.The optimization problem constructed above is a nonconvex fractional problem.This paper proposes a two-layer iterative algorithm based on Dinkelbach method,block coordinate descent method,Lagrangian dual method and continuous convex optimization technique to solve the above non-convex fractional optimization.question.After a large number of numerical simulations,the energy efficiency of the two-layer iterative algorithm proposed in this paper is higher than the results obtained by the comparative experiments.Aiming at the problem of poor signal quality of the air-ground link of UAV base stations in dense urban areas,it is proposed to be assisted by RIS deployed in dense urban areas,aiming to provide fair service for each user.This paper investigates a scenario where a deployed RIS-assisted UAV base station serves multiple users in the downlink in a dense urban area.In order to make each user get a fair service,this paper formulates a maximum-minimum rate optimization problem by jointly optimizing the communication resource allocation,RIS phase shift matrix coefficients and the horizontal position of the UAV.To deal with this non-convex optimization problem,this paper proposes an efficient iterative algorithm by exploiting block coordinate descent,semidefinite relaxation,and continuous convex optimization techniques.The final numerical results show that the algorithm proposed in this paper has the characteristics of fast convergence,and the algorithm proposed in this paper has obvious performance gains compared with the benchmark comparison experiments.