Reconfigurable Intelligent Surfaces: Principles and Opportunities

TL;DR

Reconfigurable intelligent surfaces (RISs) are a promising technology for 6G networks, capable of enhancing wireless capacity and coverage by smartly reconfiguring the environment, with extensive research on principles, performance, and integration.

Contribution

This paper provides a comprehensive overview of RIS principles, performance evaluation, machine learning applications, and integration with emerging technologies for next-generation networks.

Findings

RISs can significantly improve wireless network performance.

Machine learning techniques effectively address dynamic RIS scenarios.

Integration of RISs with other technologies offers new research opportunities.

Abstract

Reconfigurable intelligent surfaces (RISs), also known as intelligent reflecting surfaces (IRSs), or large intelligent surfaces (LISs), have received significant attention for their potential to enhance the capacity and coverage of wireless networks by smartly reconfiguring the wireless propagation environment. Therefore, RISs are considered a promising technology for the sixth-generation (6G) of communication networks. In this context, we provide a comprehensive overview of the state-of-the-art on RISs, with focus on their operating principles, performance evaluation, beamforming design and resource management, applications of machine learning to RIS-enhanced wireless networks, as well as the integration of RISs with other emerging technologies. We describe the basic principles of RISs both from physics and communications perspectives, based on which we present performance evaluation of multi-antenna assisted RIS systems. In addition, we systematically survey existing designs for RIS-enhanced wireless networks encompassing performance analysis, information theory, and performance optimization perspectives. Furthermore, we survey existing research contributions that apply machine learning for tackling challenges in dynamic scenarios, such as random fluctuations of wireless channels and user mobility in RIS-enhanced wireless networks. Last but not least, we identify major issues and research opportunities associated with the integration of RISs and other emerging technologies for applications to next-generation networks.