Intelligent Reflecting Surface Assisted Mobile Edge Computing for Internet of Things

This letter studies the impact of an intelligent reflecting surface (IRS) on computational performance in a mobile edge computing (MEC) system. Specifically, an access point (AP) equipped with an edge server provides MEC services to multiple Internet of Thing (IoT) devices that choose to offload a portion of their own computational tasks to the AP with the remaining portion being locally computed. We deploy an IRS to enhance the computational performance of the MEC system by intelligently adjusting the phase shift of each reflecting element. A joint design problem is formulated for the considered IRS assisted MEC system, aiming to optimize its sum computational bits and taking into account the CPU frequency, the offloading time allocation, transmit power of each device as well as the phase shifts of the IRS. To deal with the non-convexity of the formulated problem, we conduct our algorithm design by finding the optimized phase shifts first and then achieving the jointly optimal solution of the CPU frequency, the transmit power and the offloading time allocation by considering the Lagrange dual method and Karush-Kuhn-Tucker (KKT) conditions. Numerical evaluations highlight the advantage of the IRS-assisted MEC system in comparison with the benchmark schemes.

I. Introduction

Internet of Things (IoT) technology realizes massive connectivity for the unprecedented proliferation of smart devices, and it is now developing towards intelligent sensing and communications for the deployment of smart environments [1]. In an IoT network, a massive number of wireless devices (WDs) (e.g., sensor nodes) are deployed to connect to an access point (AP) that is capable of sensing, communications and computations. These WDs are typically capacity-limited with energy-saving low-performance processors, which have imposed a huge challenge to perform resource-intensive tasks in a low-latency manner [2]. As a result, the self-sustainable and high-performance computational capabilities are two performance metrics to deal with the challenge in IoT systems.