In order to prevent the attacker from breaking through the blockade of the interception,deploying multiple Unmanned Aerial Vehicle(UAV)swarms on the interception line is a new combat style.To solve the optimal deploym...In order to prevent the attacker from breaking through the blockade of the interception,deploying multiple Unmanned Aerial Vehicle(UAV)swarms on the interception line is a new combat style.To solve the optimal deployment of swarm positions in the cooperative interception,an optimal deployment optimization model is presented by minimizing the penetration zones'area and the analytical expression of the optimal deployment positions is deduced.Firstly,from the view of the attackers breaking through the interception line,the situations of vertical penetration and oblique penetration are analyzed respectively,and the mathematical models of penetration zones are obtained under the condition of a single UAV swarm and multiple UAV swarms.Secondly,based on the optimization goal of minimizing the penetration area,the optimal deployment optimization model for swarm positions is proposed,and the analytical solution of the optimal deployment is solved by using the convex programming theory.Finally,the proposed optimal deployment is compared with the uniform deployment and random deployment to verify the validity of the theoretical analysis.展开更多
Recently,backscatter communication(BC)has been introduced as a green paradigm for Internet of Things(IoT).Meanwhile,unmanned aerial vehicles(UAVs)can serve as aerial base stations(BSs)to enhance the performance of BC ...Recently,backscatter communication(BC)has been introduced as a green paradigm for Internet of Things(IoT).Meanwhile,unmanned aerial vehicles(UAVs)can serve as aerial base stations(BSs)to enhance the performance of BC system thanks to their high mobility and flexibility.In this paper,we investigate the problem of energy efficiency(EE)for an energy-limited backscatter communication(BC)network,where backscatter devices(BDs)on the ground harvest energy from the wireless signal of a flying rotary-wing quadrotor.Specifically,we first reformulate the EE optimization problem as a Markov decision process(MDP)and then propose a deep reinforcement learning(DRL)algorithm to design the UAV trajectory with the constraints of the BD scheduling,the power reflection coefficients,the transmission power,and the fairness among BDs.Simulation results show the proposed DRL algorithm achieves close-to-optimal performance and significant EE gains compared to the benchmark schemes.展开更多
This paper solves an energy-efficient optimization problem of a fixed-wing unmanned aerial vehicle(UAV) assisted full-duplex mobile relaying in maritime communication environments.Taking the speed and the acceleration...This paper solves an energy-efficient optimization problem of a fixed-wing unmanned aerial vehicle(UAV) assisted full-duplex mobile relaying in maritime communication environments.Taking the speed and the acceleration of the UAV and the information-causality constraints into consideration,the energy-efficiency of the system under investigation is maximized by jointly optimizing the UAV’s trajectory and the individual transmit power levels of the source and the UAV relay nodes.The optimization problem is non-convex and thus cannot be solved directly.Therefore,it is decoupled into two subproblems.One sub-problem is for the transmit power control at the source and the UAV relay nodes,and the other aims at optimizing the UAV s flight trajectory.By using the Lagrangian dual and Dinkelbach methods,the two sub-problems are solved,leading to an iterative algorithm for the joint design of transmit power control and trajectory optimization.Computer simulations demonstrated that by conducting the proposed algorithm,the flight trajectory of the UAV and the individual transmit power levels of the nodes can be flexibly adjusted according to the system conditions,and the proposed algorithm can achieve signiflcantly higher energy efficiency as compared with the other benchmark schemes.展开更多
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
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
Many extensive UAV communication networks have used UAV cooperative control.Wireless networking services can be offered using unmanned aerial vehicles(UAVs)as aerial base stations.Not only is coverage maximization,but...Many extensive UAV communication networks have used UAV cooperative control.Wireless networking services can be offered using unmanned aerial vehicles(UAVs)as aerial base stations.Not only is coverage maximization,but also better connectivity,a fundamental design challenge that must be solved.The number of applications for unmanned aerial vehicles(UAVs)operating in unlicensed bands is fast expanding as the Internet of Things(IoT)develops.Those bands,however,have become overcrowded as the number of systems that use them grows.Cognitive Radio(CR)and spectrum allocation approaches have emerged as a potential approach for resolving spectrum scarcity in wireless networks,and hence as technological solutions for future generations,from this perspective.As a result,combining CR with UAVs has the potential to give significant benefits for large-scale UAV deployment.The paper examines existing research on the subject of UAV covering and proposes a multi-UAV cognitive-based error-free model for energy-efficient communication.Coverage maximization,power control,and enhanced connection quality are the three steps of the proposed model.To satisfy the desired signal-to-noise ratio,the covering zone efficacy is investigated as a function of the distance among UAVs stationed in a specific geographic region depending on multiple deployment configurations like as rural,suburban,and urban macro deployment scenarios of the ITU-R M.2135 standard(SNR).展开更多
Unmanned aerial vehicle(UAV)has been widely used in many fields and is arousing global attention.As the resolution of the equipped sensors in the UAV becomes higher and the tasks become more complicated,much higher da...Unmanned aerial vehicle(UAV)has been widely used in many fields and is arousing global attention.As the resolution of the equipped sensors in the UAV becomes higher and the tasks become more complicated,much higher data rate and longer communication range are required in the foreseeable future.As the millimeter-wave(mm Wave)band can provide more abundant frequency resources than the microwave band,much higher achievable rate can be guaranteed to support UAV services such as video surveillance,hotspot coverage,and emergency communications,etc.The flexible mm Wave beamforming can be used to overcome the high path loss caused by the long propagation distance.In this paper,we study three typical application scenarios for mm Wave-UAV communications,namely communication terminal,access point,and backbone link.We present several key enabling techniques for UAV communications,including beam tracking,multi-beam forming,joint Tx/Rx beam alignment,and full-duplex relay techniques.We show the coupling relation between mm Wave beamforming and UAV positioning for mm Wave-UAV communications.Lastly,we summarize the challenges and research directions of mm Wave-UAV communications in detail.展开更多
Due to its high mobility and flexible deployment,unmanned aerial vehicle(UAV)is drawing unprecedented interest in both military and civil applications to enable agile and ubiquitous connectivity.Mainly operating in an...Due to its high mobility and flexible deployment,unmanned aerial vehicle(UAV)is drawing unprecedented interest in both military and civil applications to enable agile and ubiquitous connectivity.Mainly operating in an open environment,UAV communications benefit from dominant line-of-sight links;however,this on the other hand renders the communications more vulnerable to malicious attacks.Recently,physical layer security(PLS)has been introduced to UAV systems as an important complement to the conventional cryptography-based approaches.In this paper,a comprehensive survey on the current achievements of UAV-PLS is conducted.We first introduce the basic concepts including typical static/-mobile UAV deployment scenarios,the unique air-toground channel and aerial nodes distribution models,as well as various roles that a UAV may act when PLS is concerned.Then,we start by reviewing the secrecy performance analysis and enhancing techniques for statically deployed UAV systems,and extend the discussion to the more general scenario where the UAVs’mobility is further exploited.For both cases,respectively,we summarize the commonly adopted methodologies,then describe important works in the litera ture in detail.Finally,potential research directions and challenges are discussed to provide an outlook for future works in the area of UAV-PLS.展开更多
文摘In order to prevent the attacker from breaking through the blockade of the interception,deploying multiple Unmanned Aerial Vehicle(UAV)swarms on the interception line is a new combat style.To solve the optimal deployment of swarm positions in the cooperative interception,an optimal deployment optimization model is presented by minimizing the penetration zones'area and the analytical expression of the optimal deployment positions is deduced.Firstly,from the view of the attackers breaking through the interception line,the situations of vertical penetration and oblique penetration are analyzed respectively,and the mathematical models of penetration zones are obtained under the condition of a single UAV swarm and multiple UAV swarms.Secondly,based on the optimization goal of minimizing the penetration area,the optimal deployment optimization model for swarm positions is proposed,and the analytical solution of the optimal deployment is solved by using the convex programming theory.Finally,the proposed optimal deployment is compared with the uniform deployment and random deployment to verify the validity of the theoretical analysis.
基金the National Natural Science Foundation of China 61661021,61971191,61902214,and 61871321,in part by the Beijing Natural Science Foundation under Grant L182018,in part by the National Science and Technology Major Project of the Ministry of Science and Technology of China under Grant 2016ZX03001014-006in part by the open project of Shanghai Institute of Microsystem and Information Technology(20190910)+1 种基金in part by the Key project of Natural Science Foundation of Jiangxi Province(20202ACBL202006)in part by the open project of Key Laboratory of Wireless Sensor Network&Communication,Shanghai Institute of Microsystem and Information Technology,Chinese Academy of Sciences,865 Changning Road,Shanghai 200050 China,and in part by the Tsinghua University Initiative Scientific Research Program 2019Z08QCX19.
文摘Recently,backscatter communication(BC)has been introduced as a green paradigm for Internet of Things(IoT).Meanwhile,unmanned aerial vehicles(UAVs)can serve as aerial base stations(BSs)to enhance the performance of BC system thanks to their high mobility and flexibility.In this paper,we investigate the problem of energy efficiency(EE)for an energy-limited backscatter communication(BC)network,where backscatter devices(BDs)on the ground harvest energy from the wireless signal of a flying rotary-wing quadrotor.Specifically,we first reformulate the EE optimization problem as a Markov decision process(MDP)and then propose a deep reinforcement learning(DRL)algorithm to design the UAV trajectory with the constraints of the BD scheduling,the power reflection coefficients,the transmission power,and the fairness among BDs.Simulation results show the proposed DRL algorithm achieves close-to-optimal performance and significant EE gains compared to the benchmark schemes.
基金National Natural Science Foundation of China(No.61871241)Nantong Science and Technology Project(JC2019114,JC2021129).
文摘This paper solves an energy-efficient optimization problem of a fixed-wing unmanned aerial vehicle(UAV) assisted full-duplex mobile relaying in maritime communication environments.Taking the speed and the acceleration of the UAV and the information-causality constraints into consideration,the energy-efficiency of the system under investigation is maximized by jointly optimizing the UAV’s trajectory and the individual transmit power levels of the source and the UAV relay nodes.The optimization problem is non-convex and thus cannot be solved directly.Therefore,it is decoupled into two subproblems.One sub-problem is for the transmit power control at the source and the UAV relay nodes,and the other aims at optimizing the UAV s flight trajectory.By using the Lagrangian dual and Dinkelbach methods,the two sub-problems are solved,leading to an iterative algorithm for the joint design of transmit power control and trajectory optimization.Computer simulations demonstrated that by conducting the proposed algorithm,the flight trajectory of the UAV and the individual transmit power levels of the nodes can be flexibly adjusted according to the system conditions,and the proposed algorithm can achieve signiflcantly higher energy efficiency as compared with the other benchmark schemes.
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(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.
基金Ahmed Alhussen would like to thank the Deanship of Scientific Research at Majmaah University for supporting this work under Project No.R-2022-193.
文摘Many extensive UAV communication networks have used UAV cooperative control.Wireless networking services can be offered using unmanned aerial vehicles(UAVs)as aerial base stations.Not only is coverage maximization,but also better connectivity,a fundamental design challenge that must be solved.The number of applications for unmanned aerial vehicles(UAVs)operating in unlicensed bands is fast expanding as the Internet of Things(IoT)develops.Those bands,however,have become overcrowded as the number of systems that use them grows.Cognitive Radio(CR)and spectrum allocation approaches have emerged as a potential approach for resolving spectrum scarcity in wireless networks,and hence as technological solutions for future generations,from this perspective.As a result,combining CR with UAVs has the potential to give significant benefits for large-scale UAV deployment.The paper examines existing research on the subject of UAV covering and proposes a multi-UAV cognitive-based error-free model for energy-efficient communication.Coverage maximization,power control,and enhanced connection quality are the three steps of the proposed model.To satisfy the desired signal-to-noise ratio,the covering zone efficacy is investigated as a function of the distance among UAVs stationed in a specific geographic region depending on multiple deployment configurations like as rural,suburban,and urban macro deployment scenarios of the ITU-R M.2135 standard(SNR).
文摘Unmanned aerial vehicle(UAV)has been widely used in many fields and is arousing global attention.As the resolution of the equipped sensors in the UAV becomes higher and the tasks become more complicated,much higher data rate and longer communication range are required in the foreseeable future.As the millimeter-wave(mm Wave)band can provide more abundant frequency resources than the microwave band,much higher achievable rate can be guaranteed to support UAV services such as video surveillance,hotspot coverage,and emergency communications,etc.The flexible mm Wave beamforming can be used to overcome the high path loss caused by the long propagation distance.In this paper,we study three typical application scenarios for mm Wave-UAV communications,namely communication terminal,access point,and backbone link.We present several key enabling techniques for UAV communications,including beam tracking,multi-beam forming,joint Tx/Rx beam alignment,and full-duplex relay techniques.We show the coupling relation between mm Wave beamforming and UAV positioning for mm Wave-UAV communications.Lastly,we summarize the challenges and research directions of mm Wave-UAV communications in detail.
基金supported in part by the National Key Research and Development Program of China under Grant 2020YFA0711301in part by the National Natural Science Foundation of China under Grant 61922049,61941104,61921004,62171240,61771264,62001254,61801248,61971467+2 种基金the Key Research and Development Program of Shandong Province under Grant 2020CXGC010108the Key Research and Development Program of Jiangsu Province of China under Grant BE2021013-1the Science and Technology Program of Nantong under Grants JC2021121,JC2021017。
文摘Due to its high mobility and flexible deployment,unmanned aerial vehicle(UAV)is drawing unprecedented interest in both military and civil applications to enable agile and ubiquitous connectivity.Mainly operating in an open environment,UAV communications benefit from dominant line-of-sight links;however,this on the other hand renders the communications more vulnerable to malicious attacks.Recently,physical layer security(PLS)has been introduced to UAV systems as an important complement to the conventional cryptography-based approaches.In this paper,a comprehensive survey on the current achievements of UAV-PLS is conducted.We first introduce the basic concepts including typical static/-mobile UAV deployment scenarios,the unique air-toground channel and aerial nodes distribution models,as well as various roles that a UAV may act when PLS is concerned.Then,we start by reviewing the secrecy performance analysis and enhancing techniques for statically deployed UAV systems,and extend the discussion to the more general scenario where the UAVs’mobility is further exploited.For both cases,respectively,we summarize the commonly adopted methodologies,then describe important works in the litera ture in detail.Finally,potential research directions and challenges are discussed to provide an outlook for future works in the area of UAV-PLS.