Resource Allocation Algorithm Research In UAV-Assisted Cellular Network

With the development of mobile communications and the transmission of massive information,emerging communications technologies have increasingly demanded high-complexity computing resources and low-latency constraints,and demand for computationally intensive and time-sensitive applications has become increasing.Especially in the emergency communication scenario,the computing resources of the cell macro base station in the communication system are not enough to support the sudden increase in communication demand,and the computing resources and energy consumption of the mobile terminal equipment itself are also greatly restricted,and only relying on the local server can not satisfy its demand.It is difficult to complete the task in the limited time and restore the communication quality.Edge computing technology is one of the core technologies of 5G mobile communication.Deploying edge computing servers can alleviate the communication and calculation pressure of macro base stations to a certain extent,but the computing resources are limited,and edge computing servers in fixed locations can not predict emergency situations in advance.Therefore,the unmanned aerial vehicle(UAV)can equip with a server and other equipment to assist the base station.Depending on the advantages of UAV’s strong mobility and more enough computing resource,UAV can be deployed as an edge computing server and a relay to connect mobile terminal equipment to the core network for information exchange.At present,there are few considerations for joint optimization of the UAV-assisted communication system for channel bandwidth allocation,offloading strategy,and UAV distribution in the emergency communication edge computing scenario.How to make more reasonable use of the characteristics of UAV to improve the performance of the communication system is still a huge challenge.This thesis focuses on emergency communication scenarios which are based on single/multi-UAV-assisted communication with edge computing and communication resource allocation technology.The main work and research of the thesis are as follows:(1)A single UAV-assisted cellular network system in emergency situations is considered.Due to the limited energy of mobile users,a single offloading method can not meet all the task requirements.Therefore,an iterative optimization algorithm for single UAV scenario is proposed.In terms of system performance,it minimizes the total energy consumption of all mobile users in the cell by jointly optimizing the offloading strategy between the mobile users to the UAV and the central base station,and the system bandwidth allocation(the bandwidth of the drone and the base station is allocated),especially in response to the mobile terminal equipment at the edge of the cell.The system adopts the time division multiple access link mode,and the UAV can only serve one mobile user in each time slot.thereby maximizing the service efficiency of the UAV.By dividing the complex convex optimization problem into three subproblems,the service efficiency of UAV is maximized.Simulation results show that compared with the traditional strategy,the algorithm can save more energy consumption of mobile users.(2)A multi-UAV-assisted cellular network system in emergency situations is considered.Because the communication quality of mobile users needs to be guaranteed,an iterative optimization algorithm for multi UAV scenario is proposed.In terms of system performance,it maximizes the uplink transmission rate of all mobile users to identify and cover isolated mobile terminal equipments by jointly optimizing the number of UAVs in the system and their distribution,the selection of cell mobile user access links,and the bandwidth allocation of each channel.To maximize the uplink rate,the optimization problem is solved by improved clustering algorithm and linear programming.The simulation results show that the algorithm is superior to the traditional strategy in improving the total uplink transmission rate of system users,and it is more universal than the application of the traditional strategy.