Design and optimization for wireless-powered IRS-aided mobile edge computing system

A new design of intelligent reflecting surface (IRS)-aided mobile edge computing (MEC) system was studied, which consisted of a hybrid access point (HAP) connected with an MEC server, an IRS equipped with radio-frequency (RF) energy harvesting (EH) circuits, and a user side with random task arrival.To reduce energy consumption at the user, a novel protocol was proposed first, in which the system was enabled to select a proper operation mode among an EH mode, an IRS-aided task offloading mode, and an IRS-inactive task offloading mode.Then, based on the proposed protocol, an optimization problem was formulated, which aimed at minimizing the amount of consumed energy at the user by optimizing the selection of system operation mode and the resource allocation in each mode.Lyapunov optimization framework was employed to solve the problem to achieve a low-complexity and efficient optimization algorithm.Simulation results show that the proposed scheme can save 50% to 90% of energy consumption for the MEC system as c