Intelligent Reflecting Surface Aided Multigroup Multicast MISO Communication Systems

Gui Zhou,Kezhi Wang,Arumugam Nallanathan,Hong Ren,Cunhua Pan

doi:10.1109/tsp.2020.2990098

Abstract

Intelligent reflecting surface (IRS) has recently been envisioned to offer unprecedented massive multiple-input multiple-output (MIMO)-like gains by deploying large-scale and low-cost passive reflection elements. By adjusting the reflection coefficients, the IRS can change the phase shifts on the impinging electromagnetic waves so that it can smartly reconfigure the signal propagation environment and enhance the power of the desired received signal or suppress the interference signal. In this paper, we consider downlink multigroup multicast communication systems assisted by an IRS. We aim for maximizing the sum rate of all the multicasting groups by the joint optimization of the precoding matrix at the base station (BS) and the reflection coefficients at the IRS under both the power and unit-modulus constraint. To tackle this non-convex problem, we propose two efficient algorithms under the majorization--minimization (MM) algorithm framework. Specifically, a concave lower bound surrogate objective function of each user's rate has been derived firstly, based on which two sets of variables can be updated alternately by solving two corresponding second-order cone programming (SOCP) problems. Then, in order to reduce the computational complexity, we derive another concave lower bound function of each group's rate for each set of variables at every iteration, and obtain the closed-form solutions under these loose surrogate objective functions. Finally, the simulation results demonstrate the benefits in terms of the spectral and energy efficiency of the introduced IRS and the effectiveness in terms of the convergence and complexity of our proposed algorithms.

Highlights

I N THE era of 5G and Internet of Things by 2020, it is predicted that the network capacity will increase by 1000 folds to serve at least 50 billions devices through wireless communications [1] and the capacity is expected to be achieved with lower energy consumption
Extensive simulation results are provided to evaluate the performance of our proposed algorithms for an Intelligent reflecting surface (IRS)-aided multigroup multicast multiple-input single-output (MISO) communication system
By carefully adjusting the reflection coefficients at the IRS, the signal reflected by the IRS can enhance the strength of the signal received by the user

Summary

Introduction

I N THE era of 5G and Internet of Things by 2020, it is predicted that the network capacity will increase by 1000 folds to serve at least 50 billions devices through wireless communications [1] and the capacity is expected to be achieved with lower energy consumption. To meet those Quality of Service (QoS) requirements, intelligent reflecting surface (IRS), as a promising new technology, has been proposed recently to achieve high. Date of publication April 21, 2020; date of current version April 21, 2020. The associate editor coordinating the review of this manuscript and approving it for publication was Prof.

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