Research On Trajectory Design And Resource Allocation In UAV-assisted Communication

In order to provide ubiquitous connectivity and improve the quality of service for rapidly growing network devices,UAV-assisted communication technology has been widely concerned.On the one hand,hovering UAVs at a high altitude provide a high probability of establishing line-of-sight(Lo S)links between UAVs and ground devices,which further leads to improved data rate and reduced latency.On the other hand,the mobility of UAVs enables them to adjust their positions flexibly,thereby improving the network performance.However,the application of UAV-assisted communication technology still faces many challenges.It is necessary to design UAV’s trajectory properly since it is closely related to energy efficiency,latency,and throughput.What’s more,resource allocation is another important research field,which is of great significance for improving system performance.This thesis mainly studies the trajectory design and resource allocation algorithms for UAV-based relay networks and energy harvesting(EH)networks.Firstly,this thesis introduces the research difficulties of trajectory design.Then,the trajectory design and power control algorithm is studied for a point-to-point communication system based on a UAV relay.Considering the mobility constraints of UAV,the power constraints of the nodes,and the data constraint,the UAV’s trajectory and power control of source node and UAV are jointly optimized to maximize the throughput of destination node.Simulation results show that in terms of improving system throughput,the UAV-based mobile relay is superior to a traditional fixed relay,and the optimized trajectory is better than the benchmark trajectories.Secondly,in order to enhance the edge coverage of multiple cells,this thesis studies the UAV’s mobility management and user association strategy.The mobility management includes optimization of UAV’s trajectory,velocity,and acceleration.In addition,this thesis considers that the UAV has a cache to store data before forwarding them at a better position,which brings complex causal buffer constraint.The mixed-integer nonconvex problem is decomposed into two subproblems and an iterative algorithm is proposed to solve them alternately.Specifically,the mobility management problem is transformed into a convex one by applying tight bounds and relaxations and the optimal solution of user association problem is obtained by Lagrange dual method.The convergence of the algorithm is proved,and numerical simulations verify that the algorithm significantly improves the sum rate of cell-edge users with low complexity.Finally,this thesis studies a joint trajectory design and time allocation algorithm in an EH network with a UAV acting as an energy transmission source and a mobile relay.Firstly,the UAV transmits energy for energy-constrained users and collects their data,and then forwards data to the distant base station.To minimize the energy consumption of UAV,a joint optimization problem of trajectory design and time allocation is formulated based on a linear EH model.An iterative algorithm is proposed to solve the nonconvex problem.We obtain a closed-form solution of time allocation problem and transform the trajectory design problem into a convex one.Simulation results indicate that the proposed algorithm can effectively save energy consumption of UAV compared with benchmark schemes.