Research On Low-energy UAV Relay Communication

With the rapid increase in the number of mobile communication users,the pressure on cellular communication networks is also increasing.How to provide reliable communication services for large-scale mobile users has become an urgent problem for future communications.As the drone technology continues to mature,drone relay communications will likely become a future communication solution.This thesis makes in-depth study and research on the existing research of UAV relay communication networks,mainly including topics such as 3-D deployment schemes,flight trajectories,channel modeling and energy consumption issues of UAVs as relay equipment.In order to respond to the call for green communication,the paper takes the energy consumption problem of drone relay communication as the research object,and aims to improve the energy efficiency of drones.The main work of the paper is as follows:(1)The energy consumption and delay in the drone relay communication are studied.Aiming at the communication scenario of dual UAVs,the paper studies the relationship between energy consumption,delay and power.The thesis takes the minimization of energy consumption as the optimization objective,meeting the delay constraints of the user's communication requirements and the power constraints of the UAV as conditions,forming an optimization problem.Then,because the optimization problem is a non-convex problem,we use an Inner Convex Approximation(NOVA)algorithm to convert it into a strong convex problem.By solving the convex problem,the paper obtains the non-equal power allocation scheme in UAV relay communication network.Finally,after simulation analysis,this solution can effectively reduce the energy consumption of UAVs.(2)The influence of co-channel interference on drone's energy consumption in UAV relay communication is studied.Research shows that in order to meet the communication needs of users,when there is strong co-channel interference,relay drones often need to consume more energy.Therefore,this paper proposes an interference prediction and avoidance mechanism based on improved BP neural network.First,the paper improved the BP algorithm's error backpropagation update formula.Simulation results show that the improved BP neural network can improve the training speed of the neural network to a certain extent.Then,the drone will perform a certain scheduling of the flying height according to the prediction result of the co-frequency interference,so as to suppress the interference.Simulation results show that the mechanism can help drones further reduce energy consumption.