UAV-Assisted Vehicular Networks’s Trajectory And Power Allocation Design

In recent years,with the development of UAV manufacturing technology and the increasing demand of wireless communication systems,the field of UAV-assisted wireless communication has attracted the attention of experts and scholars.The UAV-assisted wireless communication system assumes an irreplaceable task in the rescue and military fields.In remote areas or when the ground communication system is overloaded,users can obtain ubiquitous communication services by assisting the communication system with UAVs.The biggest challenge of the UAVassisted wireless communication system is the limited energy on board.Therefore,it is necessary to improve system energy efficiency while improving system performance.This paper takes the UAV-assisted vehivular networks as the background to deeply study the joint optimization algorithm of the UAV flight trajectory,system power allocation scheme and the UAV and vehicle association scheme to improve the performance of the UAV-assisted vehivular networks.The main research contents and innovations of this paper are as follows:1.Aiming at the problem that fixed base stations cannot meet the performance requirements of the new generation of mobile communication systems,the UAV-assisted vehivular networks architecture is considered,and system throughput and energy efficiency optimization algorithms are proposed.In order to relieve the pressure on the backhaul link,a UAV equipped with cache unit is used to assist communication.In order to effectively improve the system throughput,an optimization algorithm is proposed to jointly optimize the flight trajectory and power distribution of the UAV.Slack variables and Taylor expansion are used to transform the non-convex optimization problem into convex optimization problem.Secondly,with the goal of improving the energy efficiency of the system,the UAV’s flight trajectory and power allocation plan are jointly optimized.Combined with transformation methods such as fractional planning,the non-convex optimization problem are solved.The simulation results show that the proposed optimization algorithms can significantly improve the system throughput and energy efficiency under constraints such as the total power of the UAV.2.Considering that more and more vehicles are connected to the Internet,only using UAVs to assist the Internet of Vehicles system is no longer sufficient to meet the needs of users.Based on coordinated multi-point transmission technology,satellite and UAV assist vehicle networking system.We propose an optimization algorithm aiming at maximizing the access rate of the vehicle.The mobile UAV is used as a relay between the satellite and the vehicle,and cooperate with the roadside base stations to provide communication services for the vehicle.Under the constraints of UAV power,mobility and information causality,considering the interference between neighboring base stations,we jointly optimize the UAV flight trajectory and system power allocation plan.In the case of a given flight trajectory,the closed solution of the optimal power distribution plan is obtained.The optimal UAV flight trajectory is obtained with a given power allocation.Based on the block coordinate descent method,the joint optimal solution of the flight trajectory and the power allocation scheme is obtained iteratively.Simulation results show that the proposed optimization algorithm can achieve the goal of green communication while improving system performance.3.Aiming at the practical application scenario of multi-vehicle two-way driving,the system architecture of UAV and satellite with cache to provide communication services for multiple vehicles is considered,and the goal is to maximize the sum of the minimum information accessibility of vehicles in the traffic flow.Under the constraints of energy consumption and information causality,the association scheme between UAV and vehicle and the flight trajectory of UAV are jointly optimized.Since the optimization problem is a non-convex mixed integer optimization problem,which is difficult to solve directly,it is decomposed into two sub-problems.First,when the UAV and vehicle association scheme is determined,the flight trajectory of the UAV is optimized.Through the first-order Taylor expansion,the global lower limit of the variable is obtained.The non-convex optimization problem is transformed into a convex optimization problem and solved by convex optimization tools.Then,the optimal UAV-Vehicle association scheme is obtained when the UAV flight trajectory is fixed.Through the introduction of auxiliary variables,the Lagrangian dual function is designed,and the optimal correlation scheme is obtained by iterative optimization.Through hierarchical iteration,the joint optimal solution of the correlation scheme and flight trajectory is further obtained.It is verified by simulation that the proposed algorithm can quickly converge and effectively improve system performance.