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....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.展开更多
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)we...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.展开更多
Unmanned Aerial Vehicles(UAV)are utilised in several security operations.However,the major limitation in utilising the UAV for security purpose is its efficiency in monitoring the targets.In real-time applications,the...Unmanned Aerial Vehicles(UAV)are utilised in several security operations.However,the major limitation in utilising the UAV for security purpose is its efficiency in monitoring the targets.In real-time applications,the flight range and number of UAVs utilised are insufficient for surveillance of the entire targets.UAVs are operated similarlyfor the flying base stations to improve the coverage rate.Utilisation of UAVs in target detection offers various benefits owing to their higher chance of line-of-sight'and monitoring at a higher altitude.The research motive of this paper is to maximise the network coverage by accurately placing UAVs under the condition of maintaining enhanced Quality of Service(QoS).This work intends to implement a Hybridized Colliding Bodies Galactic Swarm Optimization(HCBGSO)for resolving the problem of optimal placement of UAVs.The experimental outcomes demonstrate that the suggested algorithm gives better coverage,ensuring the effectiveness of the new hybrid optimisation.展开更多
基金the National Natural Science Foundation of China(No.61702258,61901211)the Natural Science Foundation of Jiangsu Province(No.BK20170766).
文摘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.
基金supported by the National Natural Science Foundation of China(61771070,61671088)。
文摘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.
文摘Unmanned Aerial Vehicles(UAV)are utilised in several security operations.However,the major limitation in utilising the UAV for security purpose is its efficiency in monitoring the targets.In real-time applications,the flight range and number of UAVs utilised are insufficient for surveillance of the entire targets.UAVs are operated similarlyfor the flying base stations to improve the coverage rate.Utilisation of UAVs in target detection offers various benefits owing to their higher chance of line-of-sight'and monitoring at a higher altitude.The research motive of this paper is to maximise the network coverage by accurately placing UAVs under the condition of maintaining enhanced Quality of Service(QoS).This work intends to implement a Hybridized Colliding Bodies Galactic Swarm Optimization(HCBGSO)for resolving the problem of optimal placement of UAVs.The experimental outcomes demonstrate that the suggested algorithm gives better coverage,ensuring the effectiveness of the new hybrid optimisation.
