Latency Minimization for Intelligent Reflecting Surface Aided Mobile Edge Computing

Tong Bai,Cunhua Pan,Yansha Deng,Lajos Hanzo,Maged Elkashlan,Arumugam Nallanathan

doi:10.1109/jsac.2020.3007035

Abstract

Computation off-loading in mobile edge computing (MEC) systems constitutes an efficient paradigm of supporting resource-intensive applications on mobile devices. However, the benefit of MEC cannot be fully exploited, when the communications link used for off-loading computational tasks is hostile. Fortunately, the propagation-induced impairments may be mitigated by intelligent reflecting surfaces (IRS), which are capable of enhancing both the spectral- and energy-efficiency. Specifically, an IRS comprises an IRS controller and a large number of passive reflecting elements, each of which may impose a phase shift on the incident signal, thus collaboratively improving the propagation environment. In this paper, the beneficial role of IRSs is investigated in MEC systems, where single-antenna devices may opt for off-loading a fraction of their computational tasks to the edge computing node via a multi-antenna access point with the aid of an IRS. Pertinent latency-minimization problems are formulated for both single-device and multi-device scenarios, subject to practical constraints imposed on both the edge computing capability and the IRS phase shift design. To solve this problem, the block coordinate descent (BCD) technique is invoked to decouple the original problem into two subproblems, and then the computing and communications settings are alternatively optimized using low-complexity iterative algorithms. It is demonstrated that our IRS-aided MEC system is capable of significantly outperforming the conventional MEC system operating without IRSs. Quantitatively, about $20~\%$ computational latency reduction is achieved over the conventional MEC system in a single cell of a $300~\rm{m}$ radius and $5$ active devices, relying on a $5$-antenna access point.

Highlights

In the multiple-device scenario, it is assumed that the devices are uniformly distributed within a circle, whose size and location are prescribed by its radius r, as well as d and d, respectively
In order to reduce the computational latency, an intelligent reflecting surfaces (IRS) was proposed for employment in mobile edge computing (MEC) systems
The benefits of using IRSs in the MEC system were evaluated under various simulation environments

Summary

Introduction

I N THE Internet-of-Things (IoT) era, myriads of machines and sensors are envisioned to be connected [1] Since these devices typically have limited computing capabilities, resource-intensive applications cannot be readily supported by these devices due to their resultant excessive computational latency. The computational latency of these resource-intensive applications can be reduced, by employing both local computing on the devices and edge computing for processing these computational tasks, provided that these tasks can be successfully off-loaded This paradigm is referred to as mobile edge computing (MEC) [3]–[14]. The devices located at the cell edge typically suffer from a low off-loading success rate, and/or their computation off-loading may impose higher latency than computing their tasks locally These devices have to rely on their own computing resources, which is often incapable of supporting resource-intensive applications. It is imperative to improve the performance of MEC systems from a communications perspective

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