Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey

This paper presents a literature review on recent applications and design aspects of the intelligent reflecting surface (IRS) in the future wireless networks. Conventionally, the network optimization has been limited to transmission control at two endpoints, i.e., end users and network controller. The fading wireless channel is uncontrollable and becomes one of the main limiting factors for performance improvement. The IRS is composed of a large array of scattering elements, which can be individually configured to generate additional phase shifts to the signal reflections. Hence, it can actively control the signal propagation properties in favor of signal reception, and thus realize the notion of a smart radio environment. As such, the IRS's phase control, combined with the conventional transmission control, can potentially bring performance gain compared to wireless networks without IRS. In this survey, we first introduce basic concepts of the IRS and the realizations of its reconfigurability. Then, we focus on applications of the IRS in wireless communications. We overview different performance metrics and analytical approaches to characterize the performance improvement of IRS-assisted wireless networks. To exploit the performance gain, we discuss the joint optimization of the IRS's phase control and the transceivers' transmission control in different network design problems, e.g., rate maximization and power minimization problems. Furthermore, we extend the discussion of IRS-assisted wireless networks to some emerging use cases. Finally, we highlight important practical challenges and future research directions for realizing IRS-assisted wireless networks in beyond 5G communications.

I. Introduction

With the popularizing of user devices constituting the future Internet of Things (IoT), we have never stopped our efforts on the challenging network optimization problems to improve the energy- or spectrum-efficiency (EE/SE) of wireless networks, with the aim of accommodating the users’ demanding data rate and diverse quality of service (QoS) requirements, e.g., [1] and [2]. Currently, the performance optimization of wireless networks either focuses on the user side or the network controller, e.g., the base station (BS) and network operator. For wireless network operators, the ever-increasing traffic demand can be fulfilled by deploying energy-efficient small cells in a dense network or using multiple antennas at the BS to increase spectrum efficiency [3]. The BS’s transmit beamforming or power allocation can be optimized to adapt to the channel variations. At the user side, multiple users can join collaboration, e.g., via device-to-device (D2D) [4] and relay communications [5]. These features can potentially provide the benefits of improved link quality and coverage, increased EE/SE performance, reduced interference and power consumption [6]. A joint optimization can be made possible when the information exchange and coordination between end users and the network controller are available. This is preferred as it generally yields a higher performance gain if it is solvable with affordable cost. Hence, numerous research works in the literature have proposed joint system optimizations to improve the EE/SE performance of wireless networks by a combination of different techniques, e.g., [7] and [8]. These may include the optimization for wireless power transfer, cooperative relaying, beamforming, and resource allocation, etc.