Research On Trajectory Optimization And Resource Allocation Of UAV Communication Network

In recent years,with the rapid development of unmanned aerial vehicle(UAV)industry,UAVs are playing a more and more important role in aerial photography and imaging,rescue and disaster relief,cargo delivery as well as surveillance and monitoring.In addition,due to the advantages of highly controllable mobility,flexibility of on-demand deployment and high probability of line of sight channels,UAV communication networks have become one of the research hotspots for the future communication networks.Numerous studies have shown that UAV communication networks can significantly improve various performance metrics compared with traditional terrestrial communication networks.However,the high probability of line of sight channels in UAV communication networks also make the potential security risks(such as eavesdropping and interference)more serious.Considering that the channel gain of the primary channel and that of the wiretap channel can be easily and effectively changed thanks to UAV’s highly controllable mobility,the physical layer security technology that safeguards the communication networks based on the difference between the primary channel and the wiretap channel has received much attention from researchers.The main contents and contributions of this paper are given as follows:(1)Considering the basic throughput-access delay tradeoff in UAV communication networks,the UAV-enabled non-orthogonal multiple access(NOMA)communication network is studied,and the sum-rate maximization problem is formulated according to the criterion of NOMA.However,this problem is a mixed integer non-convex optimization problem and involves an infinite number of optimization variables,which makes it difficult to solve directly.To solve the formulated problem,it is first proved that the optimal UAV trajectory is a fixed point,and the original optimization problem is simplified accordingly.Then,an alternating iteration algorithm based on the block coordinate descent method and the difference of two convex functions programming is proposed to optimize the UAV deployment position and the transmit power of the ground users.Finally,a low complexity heuristic algorithm is proposed based on the analytical solution to the transmit power of the ground users.The simulation results show that,compared with the separate transmit power optimization scheme and the frequency division multiple access scheme,the proposed alternating iteration scheme and the heuristic scheme can achieve similar performance and significantly improve the sum-rate of the network.(2)In order to meet the requirements of the ultra reliable and low latency communication scenarios,the UAV-enabled secure communication network in the context of finite blocklength is studied.Following the lower bound on the security capacity of the wiretap channels with finite blocklength,the average effective security rate maximization problem is constructed.However,the objective function of this optimization problem is extremely complex and the optimization variables are highly coupled,making it difficult to solve directly.To this end,the original optimization problem is first decomposed into the UAV trajectory and transmit power optimization subproblems using the block coordinate descent method.Then,these two subproblems are transformed into convex optimization problems based on the first-order Taylor approximation,respectively.Finally,an alternating iteration algorithm is proposed to jointly optimize the UAV’s trajectory and transmit power.The simulation results show that,compared with the scheme without considering the blocklength and the separate transmit power optimization scheme,the proposed j oint optimization scheme can significantly improve the average effective security rate of the network.