| With the explosive growth of the number of Internet of Things(IoT)devices around the world in recent years,wireless spectrum resources based on the fixed-allocation will become very crowded and scarce.The emergence of cognitive network technology not only can solve the problem of spectrum resource shortage,but also brings new opportunity and challenge to the expansion and fusion of wireless network in the future.In the meantime,with the unprecedented development of unmanned aerial vehicle(UAV)technology and its applications,UAV communication can improve the performance of ground wireless communication network in many aspects,such as expanding communication coverage,improving the communication efficiency and strengthening the communication capacity.So the excellent integration of UAV communication technology and traditional ground cognitive wireless network generates UAV-assisted cognitive wireless communication network,which also faces many new problems and challenges.Power shortages problem such as the UAV battery bottleneck and power tension of a large number of cognitive IoT devices cause power shortage problem which greatly affects UAV duration of flight and communication efficiency.And because the UAV-assisted cognitive wireless communication network is an open network,there are also information security problems such as monitoring information and stealing information.Therefore,under energy shortage of network system,an allocation strategy of efficient resource optimization based on UAV is designed to realize a UAV-assisted cognitive wireless communication network of low energy consumption,high energy efficiency and high security.It has become a key problem to meet the service need of ground users and improve energy efficiency,transmission efficiency and information security of the UAV-assisted cognitive wireless communication network by designing the resource allocation strategy.In order to solve the above problems,the resource allocation strategies are studied deeply from three aspects of energy consumption,transmission energy efficiency and information security for the UAV-assisted cognitive wireless communication network system.Firstly,considering the energy demand of cognitive IoT users,the UAV-assisted wireless powered communication network(WPCN)is constructed based on low energy consumption.UAV dynamic deployment is optimized in order to reduce the energy consumption of UAV and saves system energy resources.Secondly,the UAV-assisted cognitive relay network based on high energy efficiency is constructed for the requirements of medium and long distance information transmission of cognitive IoT users and transmission energy efficiency problem.Finally,in order to solve information leakage problem of IoT users for medium and long distance information transmission,the UAV-assisted cognitive relay security network is constructed.A cooperative and friendly interference mechanism based on robustness is introduced to improve the security of information transmission.With regard to the aforementioned three aspects,the specific research contents and innovations are summarized as follows:(1)The dissertation studies the resource allocation strategy of UAV assisted cognitive wireless power communication network with minimal energy consumption for the problems of UAV power shortage and energy requirement of cognitive ground IoT users without energy storage.By building the energy consumption optimization problem of rotary-wing UAV in the secondary IoT wireless power communication network,two optimal design schemes of resource allocation are proposed.Specifically,the first scheme is that a joint optimization design of UAV trajectory and user scheduling time was proposed to minimize the UAV energy consumption under the fixed UAV transmit power.At the same time,a corresponding low complexity algorithm is proposed.The simulation results show that the proposed design algorithm is superior to the flying-hovering algorithm and the traveling salesman algorithm in UAV energy consumption optimization.The second design scheme is proposed to minimize the energy consumption of the rotary-wing UAV by using a joint optimization algorithm of UAV transmit power,UAV trajectory and user scheduling time.The two proposed schemes all consider energy causality,UAV flight speed and origin-destination position constraints.The simulation results show that two proposed algorithms are effective,and also show that the second design scheme is better than the first design scheme In terms of reducing UAV energy consumption,so as to further improve the energy utilization of the whole secondary network.(2)After completing power supply of cognitive IoT ground users,a UAV-assisted cognitive relay network is constructed for the requirements of secondary IoT users about medium and long distance information transmission,the serious attenuation problem of ground information transmission and the problem of low transmission efficiency.Under the limited energy of UAV,this dissertation studies the resource allocation strategy of the UAV-assisted cognitive relay network with high energy efficiency.The dissertation puts forward a kind of alternating and iterative optimization algorithm by jointly optimizing three-dimensional trajectory of UAV and transmission power.Specifically,the three-dimensional trajectory of UAV relay and transmit power of UAV and secondary IoT user are jointly optimized to maximize the information throughput of secondary destination IoT user,under meeting UAV speed and height limit,maximum power and average power limit,information causal limit and interference temperature(IT)threshold limit.Under the throughput maximization algorithm of three-dimensional trajectory optimization,an alternate and iterative joint algorithm for energy efficiency maximization based on block coordinate descent and Dinkelbach method was further proposed.By minimizing UAV energy consumption and maximizing the information transmission throughput of secondary IoT user in the cognitive relay network,the energy efficiency of the UAV-assisted cognitive relay network can be maximized in order to improve energy utilization and information transmission efficiency.In the dissertation,the path and time discretization technique,the continuous convex approximation technique and the alternate optimization method of subproblems are used to solve difficult and non-convex problems.Simulation results show that the proposed alternate optimization algorithm has fast convergence and effectiveness.And it is also proved that the proposed algorithm based on three-dimensional trajectory optimization is superior to existing optimization algorithms of two-dimensional trajectory in terms of performance.(3)On the basis of the establishment of UAV cognitive relay network of high energy efficiency and UAV energy limit,the dissertation studies the resource allocation strategy of UAV-assisted cognitive relay secure network with high security due to the information insecurity problems such as information monitoring or information stealing.For the insecurity problem of information which is eavesdropped in the process of information transmission between IoT users in the secondary network,the system model of cognitive relay network physical layer security based on friendly cooperative interference UAV is modeled,and the original optimization problem of the average security rate maximization of the secondary relay network in the worst case is constructed.A jointly iterative optimization algorithm for dual UAVs trajectory resources and power resources is proposed based on the robustness of eavesdropper position.The non-convex original optimization problem is decomposed into three sub-optimization problems.The approximate optimization solution of the original optimization problem is obtained by using continuous convex approximation technique and alternate optimization method.Compared with other algorithms,the simulation results show that the proposed algorithm can significantly improve the information security rate,and further confirm the convergence and validity of the proposed algorithm and the correctness of the theoretical analysis. |
PDF Full Text Request