In this paper,we consider the scenario of using unmanned aerial vehicles base stations(UAV-BSs)to serve cellular users.In particular,we focus on frnding the minimum number of UAV-BSs as well as their deployment.We pro...In this paper,we consider the scenario of using unmanned aerial vehicles base stations(UAV-BSs)to serve cellular users.In particular,we focus on frnding the minimum number of UAV-BSs as well as their deployment.We propose an optimization model which minimizes the number of UAV-BSs and optimize their positions such that the user equipment(UE)covered ratio is no less than the expectation of network suppliers,the UEs receive acceptable downlink rates,and the UAV-BSs can work in a sustainable manner.We show the NP-hardness of this problem and then propose a method to address it.The method first estimates the range of the number of UAV-BSs and then converts the original problem to one which maximizes the UE served ratio,given the number of UAV-BSs within that range.We present a maximizing algorithm to solve it with the proof of convergence.Extensive simulations based on a realistic dataset have been conducted to demonstrate the effectiveness of the proposed method.展开更多
基金supported by the National Natural Science Foundation of China(61903076,61773109)Liaoning Revitalization Talents Program(XLYC1807009)
文摘In this paper,we consider the scenario of using unmanned aerial vehicles base stations(UAV-BSs)to serve cellular users.In particular,we focus on frnding the minimum number of UAV-BSs as well as their deployment.We propose an optimization model which minimizes the number of UAV-BSs and optimize their positions such that the user equipment(UE)covered ratio is no less than the expectation of network suppliers,the UEs receive acceptable downlink rates,and the UAV-BSs can work in a sustainable manner.We show the NP-hardness of this problem and then propose a method to address it.The method first estimates the range of the number of UAV-BSs and then converts the original problem to one which maximizes the UE served ratio,given the number of UAV-BSs within that range.We present a maximizing algorithm to solve it with the proof of convergence.Extensive simulations based on a realistic dataset have been conducted to demonstrate the effectiveness of the proposed method.
