Research On Trajectory Optimization And Resource Allocation Scheme In UAV-Assisted Iot Networks

The Internet of Things(IoT)aims to build an information interaction network with ubiquitous coverage and seamless interconnection,evolving towards the coexistence of multiple services and the full connection of communication terminals.However,due to the difficult construction,long deployment periods,high operating costs and poor flexibility,it is difficult for traditional terrestrial infrastructures to guarantee the communication requirements of IoT devices in special scenarios,such as emergencies or remote areas.Thanks to the advantages of low cost,convenient deployment,flexible movement and establishment of line-of-sight links,unmanned aerial vehicles(UAVs)can fly to designated areas and provide on-demand,flexible and reliable communication services,thereby effectively making up for the deficiencies of existing terrestrial communication networks.Therefore,the research and application of UAVs to assisted IoT networks has recently attracted extensive attention.Through the reasonable planning of the UAV flight trajectory and resource allocation,the problem of coverage blindness has been effectively solved and more flexible and diverse applications have been realized in the IoT networks.However,the characteristics of diversified business scenarios and differentiated performance demands bring new challenges to researches on UAV-assisted IoT networks.How to design the flight trajectory and resource allocation of UAVs to support the diverse business scenarios and meet their differentiated performance requirements is one of the key issues in achieving the goal of internet of everything.Therefore,this thesis studies two typical scenarios in UAV-assisted IoT networks and proposes differentiated service demand-based and heterogeneous service quality of service-guaranteed UAV trajectory optimization and resource allocation schemes,respectively.The main work of the thesis is as follows:In this thesis,a quality of X(QoX)evaluation model and a servicedemand-based hierarchical networking scheme are proposed for the differentiated device service requirements in the UAV-assisted IoT network.Specifically,the QoX model takes a comprehensive consideration of service priority,data rate,completeness and up-to-dateness parameters.A QoX-oriented device hierarchical architecture is constructed.Then,based on this architecture,UAVs are deployed sequentially layer by layer,with bandwidth reserved for lower-layer devices.On the premise of ensuring a robust UAV network,the UAV location,device association and bandwidth allocation are jointly optimized with the objective of minimizing the number of UAVs required.To solve the problem,a problem transformation-based improved particle swarm optimization algorithm is proposed.Simulation results show that compared with the benchmark algorithms,the proposed scheme can reduce the number of UAVs while meeting the differentiated demands of the devices.In addition,according to the service demands,the proposed scheme can dynamically adjust the optimal reservation ratio.In this thesis,a cooperative UAV trajectory optimization and resource allocation scheme for enhanced mobile broadband(eMBB)user data rate improvement is proposed to solve the problem of eMBB rate loss in the UAV-assisted IoT network with coexisting eMBB and ultra-reliable and low latency communication(URLLC)services.In the proposed scheme,a major UAV is employed to serve both the URLLC and eMBB users,and an auxiliary UAV with predetermined missions is assigned to provide supplementary services.The punctured eMBB users are served by the two UAVs simultaneously.On the premise of ensuring the quality of service requirements for both URLLC and eMBB services,the UAV trajectory,puncturing association and bandwidth allocation are jointly optimized.The problem is solved through a block coordinated descent-based iterative algorithm.Simulation results show that compared with the benchmark algorithms,the proposed scheme can improve the data rate of eMBB users,while ensuring the minimum quality of service requirements of URLLC and eMBB users.