Deployment And Communication Resource Allocation Of UAV Ad Hoc Networks Based On Cyber Physical Fusion

Unmanned aerial vehicles(UAVs)ad hoc networks are hot research topics in the application and communication areas of UAVs,which have aroused extensive attention of scholars.UAVs are equipped with computation,communication and control modules,which play key roles in UAV ad hoc networks.On one hand,UAVs focus on building a closed loop consisting of environmental perception,information interaction,decision making and precise execution,so as to combine the cyber domain dominated by communication and computation with the physical domain dominated by sensing and control.On the other hand,computation,communication and control depend on and promote each other in a coupling way.For example,communication is necessitated to obtain the data needed for computation and form consensus decisions.Flying control keeps the network connected.Computation can empower communication and control.Therefore,the joint planning on communication,computing and control from the cyber-physical fusion perspective is expected to promote the development of UAV ad hoc networks.However,the cyber physical model specific to UAV ad hoc networks has not be built,which can guide the optimal configuration of resources.In the aspect of military applications,deploying UAV ad hoc networks as aerial backbone networks to provide flexible communication coverage for ground users is promising.However,there are two key issues which have not been well solved.One is how to select the optimal locations for UAVs and the other is how to allocate communication resources to improve the network performance.In fact,the optimal deployment and resource allocation need to comprehensively utilize the resources and information of cyber and physical domains,which can be performed under the guidance of the cyber physical model.To sum up,in view of the tight coupling between the cyber domain and physical domain,this thesis focuses on improving the system efficiency and communication performance of UAV ad hoc networks under the scenario where UAVs work as aerial base stations.Specifically,the modeling,deployment optimization and communication resource allocation are studied from the perspective of cyber physical fusion.The main works and contributions are summarized as follows:To evaluate the system efficiency and alleviate the communication bottleneck of UAV ad hoc networks,this thesis proposes two cyber physical models from the perspective of system efficiency and communication performance,respectively,which are expected to guide the resource allocations in cyber domain and physical domain.The former is based on the overall system efficiency.Firstly,the control,communication and computation processes of UAV ad hoc networks are respectively modeled.Then,a general system efficiency-oriented model is proposed,which not only quantifies contributions of the three aspects to the task efficiency,but also provides theoretical guidance for the allocation of multi-dimensional and limited resources.Considering the different demands of UAVs on the performance of each aspect and the overall performance in different scenarios,parameter interfaces are set in the model.The latter focuses on the communication performance.Firstly,a communication framework based on the cyber physical fusion is constructed which extends the dimensions of communication decisions to computation and control,and thus can orient the environmental changes precisely and make targeted communication decisions.Then,taking the energy consumption as the performance metric,the energy consumption optimization model for the jointly planning of communication,computation and control is established,which provides references for the design of communication protocols and algorithms in actual systems.Simulation results show that the proposed system efficiency-oriented model can accurately represent the comprehensive contributions of communication,computation and control to the system,as well as can guide the allocation of limited resources among the three aspects to achieve the optimal system effeciency.The proposed communication performance-oriented model can support the joint optimization of communication,control and computation,and thus significantly reduce the energy consumption and delay of UAV communication.For the problem of deploying UAV ad hoc network to provide on-demand communication coverage for ground users,this thesis designs a centralized and low-complexity deployment algorithm which minimizes the number of UAVs while ensuring the connectivity of the UAV ad hoc network.Firstly,discrete UAV candidate locations are selected according to the geographical distribution of ground users,and the deployment problem is modeled as minimization of the number of UAVs.Considering the modeled problem belongs to integer nonlinear programming problem which is NP-hard,a heuristic centralized deployment algorithm is proposed to reduce the complexity.The proposed algorithm firstly selects UAV candidate locations according to user distribution;then,iteratively deletes redundant locations under the constraints of ensuring users’ quality of service(Qo S),connectivity of the backbone network and coverage ratio;and finally,obtains the optimal deployment locations.Therefore,the optimal deployment results can be acquired with low time complexity.In the process of deleting redundant locations,information isolation island detection and retrospecting mechanisms are introduced to ensure the connectivity of backbone network and further reduce the number of UAVs.Simulation results show that the proposed centralized algorithm can obtain the optimal deployment results close to the theoretical minimum while guaranteeing the Qo S of users and the connectivity of the backbone network.Therefore,the on-demand coverage for the ground users can be realized while the deployment cost is reduced.For the problem of deploying UAVs to assist ground base stations to provide ondemand communication coverage for ground users,a hybrid optimization algorithm consisting of the centralized and distributed algoritms is proposed to achieve the optimal deployment of UAVs quickly,which minimizes the number of UAVs and maximizes the load balance while ensuring network robustness.To improve the robustness of UAV backbone network,the network bi-connection mechanism is introduced and its superiority in ensuring network robustness is proved.Firstly,the multi-objective optimization problem is constructed to minimize the number of UAVs and maximize the load balance.Then,the problem is decomposed into two sub-problems,namely,the problem of minimizing the number of UAVs for given user distribution and the problem of maximizing the load balance for given number of UAVs.A hybrid deployment algorithm is proposed to solve the problem step by step,where the centralized greedy search algorithm is firstly utilized to obtain the minimum number of UAVs and suboptimal positions in discrete space,and then the distributed motion algorithm based on artificial potential field is used to search the optimal UAV locations in continuous space.To ensure the seamless connection between UAV and existing backbone network,the penetration flight and new virtual connection line establishment mechanisms are designed in the distributed algorithm.Simulation results show that,compared with the centralized algorithm and distributed algorithm,the hybrid optimization algorithm can achieve the optimal deployment with a lower time complexity.Specifically,the number of UAVs close to the theoretical minimum,and the maximum load balance close to 1 are harvested.For the three-dimensional resource allocation problem in time,space and power domains,the link Qo S,fairness and priority are jointly considered,and two algorithms,i.e.,the dual-based iterative search algorithm(DISA)and sequential exhaustive allocation algorithm(SEAA),are proposed to jointly optimize the slot allocation,antenna boresight and transmit power.To fit the characteristics of UAV such as 3D communication,high dynamicity and mission complexity,a 3D radiation model for the directional antenna and a block fading channel model containing both large and small scale fading are adopted.Firstly,the UAV networking process is modeled as the periodic point-to-point communication link scheduling process,and a concurrent transmission media access control(MAC)protocol based on cyber physical fusion is proposed.Then,fairness and priority strategies are introduced to model the communication resource allocation problem as maximization of the fairness-weighted network capacity.The formulated problem belongs to the mixed integer nonlinear programming problem which is NP-hard.Next,to reduce the complexity of solving it,two algorithms,i.e.,DISA and SEAA,are proposed to obtain the optimal solution approximately.DISA firstly transforms the primal problem into a continuousvariable optimization problem by relaxing the slot allocation variable,and then adopts the Lagrangian duality theory to approximately solve the problem.SEAA schedules links in order,i.e.,from high priority ones to low priority ones,which reduces the computational complexity.Besides,the exhaustive idea is adopted which ensures the optimality of the results.Simulation results show that the proposed two algorithms can efficiently achieve the optimal resource allocation.Specifically,the network capacity is maximized while the priority and fairness of links are ensured.