| With the rapid development of the Internet of Vehicles,the continuous emergence of a large number of new service applications such as unmanned intelligent driving,in-vehicle ultra-clear video,and augmented reality has put forward higher requirements for the communication and computing capabilities of the Internet of Vehicles system.At the same time,the link instability problem between the roadside unit and the vehicle due to the high-speed mobility of the vehicle is also a challenging and critical research task.Millimeter waves are located in the 30-300 GHz frequency band.Applying its rich bandwidth resources to the Internet of Vehicles will greatly improve the communication performance of the existing Internet of Vehicles systems.Therefore,this paper combines 5G Internet of Vehicles with millimeter wave communication technology,and deeply studies the communication and computing resource allocation of 5G Internet of Vehicles,so as to provide more secure and reliable services for vehicle users.This paper mainly carries out the following three aspects of work:(1)A heuristic algorithm for joint optimization of resource and task offloading is proposed.Firstly,focus on the problem of vehicle task offloading decision and communication resource allocation in the highway scene,and establish a resource allocation problem with the optimization goal of minimizing the average task completion time,and the task offloading ratio and resource blocks as the optimization variables.Since the original optimization problem is a 0-1 mixed integer nonlinear programming problem,it is difficult to solve it directly using conventional convex optimization algorithms.Therefore,the original optimization problem is decoupled into the resource block allocation sub-problem and the offloading decision sub-problem,and the sub-problems are solved by using the water injection algorithm and the particle swarm algorithm respectively.Then,the subproblems are iteratively solved based on the heuristic algorithm to obtain the optimal resource block allocation scheme and offloading decision vector.Simulation results show that the algorithm minimizes the average system delay while satisfying all vehicle mission requirements.(2)Aiming at the frequent handover of the millimeter-wave communication link between the vehicle and the 5G millimeter-wave micro-base station caused by the high-speed mobility of the vehicle in the highway scene,a highly reliable on-board task offloading algorithm based on matching theory is proposed.Considering the impact of time delay and energy consumption on task offloading,an optimization model is established with the vehicle terminal benefit as the optimization goal.The5 G millimeter-wave micro base station and vehicle terminal can be regarded as matching objects,and a vehicle task offloading algorithm based on many-to-one matching is proposed to solve the optimization problem.The simple road condition of the highway brings great convenience to the vehicle trajectory prediction,so the algorithm selects the optimal mm Wave beam for the vehicle in advance before the vehicle terminal sends the handover,and based on the benefit of the vehicle terminal after the beam prediction specifies the task offload policy.The simulation results show that the algorithm can achieve good performance in terms of delay and energy consumption,and can achieve higher user benefits.(3)A task offloading management and control platform for the MEC and 5G micro base station fusion system is designed and developed.The MEC server offloads the user services that meet the conditions to the local server for processing through the task offloading and offloading policies issued,which not only reduces the task completion delay but also reduces the load pressure on the core network.In addition,based on the intelligent terminal information obtained by the 5G micro base station,the users accessing the base station are matched with the authentication table of the background database to limit user service requests. |
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