Research On Optimization Of Mobile Edge Computing And Wireless Power Supply Network Assisted By Intelligent Reflective Surfac

With the development of modern information technology,the number of Internet of Things(IOT)devices has experienced an explosive growth,which has brought huge challenges to the data computing and energy supply of existing networks.The introduction of mobile edge computing(MEC)into the network can effectively relieve computing pressure and the performance of the system;When the channel is severely faded or blocked,the intelligent reflecting surface(IRS)can be used to modify the channel conditions to meet the communication requirements of low-power IOT devices;Wireless power communication network(WPCN),as an example to solve the problem of insufficient power supply,provides continuous and stable energy for the normal operation of IOT devices.This paper is based on the IRS-assisted MEC system and wireless power communication network,and sets the protocol,builds the system model,designs the algorithm solution,and simulates the verification analysis to realize the maximum computation energy efficiency and throughput of the corresponding system/network respectively.(1)For the case that the non-orthogonal multiple access(NOMA)does not guarantee the data reach the receiver side at the same time in IRS-assisted MEC system when the channel conditions and data sizes of users are different;this paper considers the hybrid NOMA transmission mode to achieve the maximum computation energy efficiency.Since the optimization process involves non-convex fractional programming problems that are difficult to solve,this paper proposed a Dinkelbach-SCA algorithm with two iterative steps: Firstly,this paper converted the initial problem into a tractable form via Dinkelbach’s method,optimization of IRS discrete phase shift by separating variables.Then,by introducing auxiliary variables,and leveraging successive convex approximation(SCA),the paper decoupled the relationship between transmit power and time while converted the non-convex problem to a convex one.Hence,the paper can obtain the optimal solution.The simulation results show that the energy efficiency of the system scheme in this paper is better than other comparison ones,and the energy efficiency of the system increases with the decrease of the minimum computational data amount of user 2.(2)In the scenario of energy shortage of IRS and IOT devices,there is insufficient research on hybrid backscatter and active communication mode.In this paper,we consider the IRS-assisted WPCN,which sets the IRS and IOT devices energy-limited,to complete the wireless power transfer of the network and the data transmission in hybrid backscatter and active communication mode.In order to maximize the throughput in the network,the power transmitted by the power station and the phase shift of the IRS in backscatter and active communication are first analytically obtained;Then,the introduction of auxiliary variables to decouple the power and time of active communication;Finally,the semidefinite relaxation(SDR)algorithm and the iteration algorithm are proposed to optimize the coupling of IRS phase shift and time during the power transfer phase to achieve the resource allocation of the network.Simulation results show that the hybrid transmission mode used in this paper has a more obvious performance advantage compared with the iterative scheme of a single transmission mode in the case of insufficient power supply for IRS and IOT devices;and the hybrid transmission mode iterative scheme is close to the performance of the SDR scheme.