Research On Mobile Edge Computing Optimization Based On IRS-assisted Joint Offloading And Computin

In recent years,with the proliferation of 5G,the explosive growth of data,the high complexity of networks,the increasing energy consumption and hardware costs have become critical challenges for future mobile communications,which also pose greater challenges for the design of communication systems.Scholars have proposed a number of technologies and response plans.Among them,Orthogonal Frequency Division Multiplexing(OFDM)and Cooperative Relaying are important technologies to improve wireless communication spectrum efficiency,which have been widely used in 4G and 5G wireless communication systems.Intelligent Reflected Surface(IRS)technology can break the traditional wireless communication passive optimization channel quality constraints,and can significantly improve the spectrum efficiency of wireless communication,with low cost,low energy consumption,programmability,easy deployment and other characteristics,which has been favored by scholars and enterprises.On the other hand,mobile edge computing technology is a new technology that can improve the computing power of mobile terminals and achieve low-latency communication and is being widely used,such as VR/AR,unmanned driving,etc.Therefore,in order to save the energy consumption of mobile edge computing(MEC)system,this thesis takes the MEC system based on IRS-assisted communication and OFDM cooperative relay as the research object and conducts in-depth research on its joint task offloading and computation scheme from the aspects of model and protocol design,problem modeling and solution,and system performance simulation.Firstly,the task offloading protocol design scheme of the MEC system based on IRS-assisted communication and OFDM cooperative relay was studied,and a new protocol that can effectively use IRS-assisted communication to improve task offloading spectrum efficiency was proposed.Then,based on the proposed protocol,the corresponding system optimization problem was established considering the task computing time delay constraint.By jointly optimizing the reflection coefficient of the reflection unit,subcarrier allocation,power allocation and task allocation of the user terminal and the relay node,the total energy consumption of task offloading and computation of the user terminal and the relay node was minimized.Since the subcarrier allocation optimization of the user terminal is an integer programming problem,and the optimization of the reflection coefficient of the reflection unit is a quadratic optimization problem,the resource allocation optimization problem is a difficult problem to solve,which is a mixed integer quadratic programming non-convex problem.In order to solve this problem,this study simplified the optimization problem into two subproblems of integer programming and quadratic retrieval optimization.Specifically,first,under the given reflection coefficients,an iterative optimization algorithm that can approach the lower bound performance was proposed by using the continuous relaxation method and continuous convex approximation method.Second,under the given subcarrier allocation,power allocation,task allocation,task offloading time and computation time allocation,the variable substitution method with lower complexity was used to simplify the quadratic programming problem about the reflection coefficient,and the sub-optimal feasible solution of the retrieval problem reflection coefficient was obtained.Finally,the alternate iterative optimization method was used to iteratively obtain the feasible solution of the system that can approach the lower bound performance.Simulation results show that compared with the traditional scheme without IRS and other benchmark schemes,the proposed IRS-assisted joint cooperative task offloading and computation scheme can significantly reduce the total energy consumption of the system,thus verifying the importance of IRS-assisted communication technology in wireless communication.