Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network

IRS is a new and revolutionizing technology that is able to significantly improve the performance of wireless communication networks, by smartly reconfiguring the wireless propagation environment with the use of massive low-cost passive reflecting elements integrated on a planar surface. Specifically, different elements of an IRS can independently reflect the incident signal by controlling its amplitude and/or phase and thereby collaboratively achieve fine-grained 3D passive beamforming for directional signal enhancement or nulling. In this article, we first provide an overview of the IRS technology, including its main applications in wireless communication, competitive advantages over existing technologies, hardware architecture as well as the corresponding new signal model. We then address the key challenges in designing and implementing the new IRS-aided hybrid (with both active and passive components) wireless network, as compared to the traditional network comprising active components only. Finally, numerical results are provided to show the great performance enhancement with the use of IRS in typical wireless networks.

Introduction

The targeted 1000-fold network capacity increase and ubiquitous wireless connectivity for at least 100 billion devices by the forthcoming fifth-generation (5G) wireless network have been largely achieved, thanks to the various key enabling technologies such as ultra-dense network (UDN), massive multiple-input multiple-output (MIMO), millimeter wave (mmWave) communication, and so on [1]. However, the required high complexity and hardware cost as well as increased energy consumption are still crucial issues that remain unsolved. For instance, densely deploying base stations (BSs) or access points (APs) in a UDN not only entails increased hardware expenditure and maintenance cost, but also aggravates the network interference issue. In addition, extending massive MIMO from sub-6 GHz to mmWave frequency bands generally requires more complex signal processing as well as more costly and energy consuming hardware (e.g., radio frequency (RF) chains). Therefore, research on finding innovative, spectral and energy efficient, and yet cost-effective solutions for future/beyond-5G wireless networks is still imperative [2].