Research On Task Offloading And Caching Strategy For NOMA-MEC-based Cooperative Vehicle Infrastructure System

In the 5G era,the Internet of Vehicles(Io T)technology is developing rapidly.As an important application scene of the Intelligent Transportation System(ITS),the construction and improvement of the vehicle-road cooperative system is an important step in the evolution of ITS.Through the intelligent communication cooperation between vehicles and road infrastructure,the vehicle-road cooperative system promotes the development of ITS from vehicle intelligence to vehicle-road intelligence.Mobile Edge Computing(MEC)is the key technology to realize the intelligent communication.Through MEC-based vehicle-road cooperative task offloading,vehicle can offload task to the Road Side Unit(RSU)for edge computing,reducing the delay and energy consumption.However,the requirement for Ultra-Reliable and Low-Latency Communication(URLLC)and the characteristic of vehicle’s constantly movement make vehicle-road cooperative task offloading a challenge.In addition,many technologies can further reduce the delay and power consumption of task offloading.For example,Non-Orthogonal Multiple Access(NOMA)can improve frequency band utilization through channel multiplexing.Content caching enables the deployment of caching service to avoid the overhead of repetitive tasks.By combining the above technologies,it is of great significance to construct a vehicle-road cooperative system that can realize efficient task offloading under the dynamic scene of the Io V and the requirement of reliability.We study the task offloading and caching strategy for NOMA-MEC-based cooperative vehicle infrastructure system.The main work is as follows:Firstly,we aim at the vehicle-road cooperative task offloading problem under the constraints of vehicle mobility and reliability.To solve this problem,we propose a task offloading strategy with vehicle clustering under NOMA.Specifically,we establish a NOMA-MEC-based vehicle-road cooperative system,including communication model,computing model,vehicle-mobility model and reliability model.Then based on the proposed system,we formulate the vehicle-road cooperative task offloading optimization problem,and analyze its two key constraints,i.e.the constrain of vehicle mobility and the constrain of reliability.The mobility constraint is modeled by vehicle-residence-time and vehicledeparture-time.Besides,the reliability is guaranteed by the constraints of SINR threshold and communication interruption probability.In order to maximize the utility of vehicle-road cooperative system,we jointly optimize vehicle clustering under NOMA,vehicle transmit power and task offloading decision,and propose the joint algorithm for vehicle clustering,power control and offloading decision(JACPO)to solve the mixed integer nonlinear optimization problem.Firstly,the max-cut problem of graph theory is utilized to optimize vehicle clustering and transmit power,and then the offloading decision is jointly optimized by game theory.The numerical simulation shows that the proposed strategy can effectively improve the utility of the cooperative vehicle infrastructure system under different vehicle speeds and reliability,Besides,the optimization performance of our proposed strategy is better than other comparison strategies.Secondly,we aim at the problem that limited computing resources of RSU lead to increased task delay and energy consumption in the process of vehicle-road cooperative task offloading.To solve this problem,we propose a vehicle-road cooperative task offloading strategy combining content caching and vehicle clustering under NOMA.Specifically,we establish a NOMA-MEC-based vehicle-road cooperative system utilizing content caching,including communication model,cache model and computing model.In the proposed system,RSU deploys cache service at the edge side,which reduces the delay and energy consumption of vehicle-road cooperative task offloading in the scene of large traffic flow.Then we formulate the optimization problem of vehicle-road cooperative task offloading combining content caching and vehicle clustering under NOMA,and propose the joint algorithm for vehicle clustering,power control,offloading decision and caching strategy(JACPOC)to solve this problem.Firstly,the clustering and transmit power of vehicles under NOMA are optimized,and then offloading decision and caching strategy are solved utilizing the particle swarm optimization theory.The numerical simulation shows that the vehicle-road cooperative system utilizing content caching can further improve the system utility,and the proposed strategy has better optimization performance than other comparison strategies.