Coverage Optimization And Robust Routing Selection For Hierarchical UAV Network

Due to the advantages of low cost,easy deployment and the flexibility to perform various tasks,unmanned aerial vehicle(UAV)gets widely attention in the field of certain civil or military.Even in some areas,the applications of the unmanned aerial vehicle are far beyond our imagination.Therefore,this paper focuses on the topic of coverage Optimization and robust routing selection for hierarchical UAV network.The main contributions of this thesis are as follows:Firstly,when traditional long-term and time-consuming cellular network planning is unavailable,a novel cooperative two-layered UAV network architecture is proposed to minimize the transmission delay and maximize the packet delivery ratio.Moreover,the coverage optimization problem is formulated as an effective coverage time maximization problem.And the optimal coverage results are achieved by closed-form coverage boundaries analysis.Correspondingly,an optimal routing scheme is proposed called Partial Delay Matrix Eigenvalues(PDME)routing algorithm to reduce the link delay and packet loss ratio.Finally,numerous results are analyzed to verify the performance of proposed coverage and routing optimization algorithms,Secondly,a cube based space region partition(CSRP)routing algorithm is proposed to solve the problem of efficient routing selection in high density UAV network,which reduces end-to-end average delay and improve the delivery ratio.Finally,numerous results verify the performance of proposed routing algorithm with AODV routing algorithm and GPSR routing algorithm,in terms of end-to-end average delay,delay jitter,and delivery ratio.