The Research Of Uav-Assisted Network Resource Alloca-Tion Algorithm Based On Wireless Power Transfer

The Fifth Generation Mobile Communication(5G)technology aims to achieve ubiquitous communication,and meet the increasing demand for mobile user terminal equipment and wireless data transmission for mobile communication services,such as artificial intelligence,high-definition video,etc.However,in some special scenarios,such as temporary hotspots or disaster areas,it is often difficult to guarantee the communication quality due to the difficulty and high cost of deploying ground base stations.Unmanned aerial vehicle(UAV)-assisted network can support wireless communication,where the UAV equipped with communication equipment acts as flying base station or relay.With advantages of high mobility,high flexibility and low cost,it has attracted wide attention in recent years.UAV-assisted networks can provide quick and convenient wireless communication services in many scenarios where network coverage is currently difficult to achieve.It can expand network coverage or improve the system performance.Meanwhile,it also brings a series of problems and challenges,such as increased interference,limited service life,and complex deployment.In UAV-assisted networks,service time is limited due to the limited battery energy of the UAV.How to plan and design UAV's location,allocate wireless resources reasonably,and extend the life of UAV s are key issues in the UAV-assisted networks.Therefore,this thesis studies two typical scenarios of introducing wireless energy transfer in the UAV-assisted network.This thesis proposes a UAV deployment and resource allocation algorithm based on user quality of service(QoS)in the downlink scenario,where the UAV acts as relay.Considering the UAV's limited energy,the simultaneous wireless information and power transfer(SWIPT)technology based on power splitting is introduced to charge the UAV.The optimization goal is to minimize the UAV's energy consumption on the premise of meeting the user's data rate requirements,where the power splitting ratio and time switching ratio are optimized.At the same time,considering the impact of the location of the UAV on the quality of the downlink channel,the power splitting ratio,time allocation ratio,and three-dimensional deployment of the UAV are jointly optimized to establish the UAV energy consumption model and solve the energy consumption minimization problem.Then,the concept of particle is introduced to simplify the complexity of the algorithm for the optimal position of the UAV.Simulation results show that the proposed algorithm can effectively reduce UAV energy consumption compared with existing UAV resource allocation algorithms which introduce SWIPT technology,while ensuring user data rate.And the proposed algorithm can dynamically adjust the resource allocation ratio according to user needs.The thesis proposes a UAV trajectory and resource optimization algorithm for improving the reliability of the data transmission in the UAV relay uplink scenario.Sensors are limited by energy,as the result transmit power is small,and the transmission is easily interrupted in some cases,such as long distance from the base station.In order to improve the uplink communication quality of sensor networks,the UAV is used as relay between sensors and base station.The average probability of network interruption is minimized and the reliability of network transmission is improved while introducing wireless energy transmission technology and using charging piles to charge UAV and sensors.Considering that charging and communication can't be performed at the same time,and the sensor is connected to the UAV by time division multiplexing.When allocating the time slot allocation,we not only consider the transmission power limitation of the charging time slot,but also pay attention to the sensor association problem.Therefore,the slot allocation,power allocation and UAV flight trajectory are jointly optimized,and the average outage probability model of the network is established and solved by an iterative algorithm.Simulation results show that the proposed algorithm can effectively reduce the average probability of network interruption and ensuring the UAV energy consumption compared to the circular trajectory algorithm.