Reconfigurable Intelligent Surfaces for 6G Mobile Networks: An Industry R&D Perspective

TL;DR

This paper discusses the development, industry perspectives, and technical challenges of reconfigurable intelligent surfaces (RIS) for 6G networks, focusing on liquid crystal-based RIS, modeling approaches, and deployment strategies.

Contribution

It provides industry-oriented insights, a hardware design at 28 GHz, and models for RIS deployment and optimization in 6G networks, integrating AI/ML techniques.

Findings

Large RIS improves coverage significantly.

Higher frequencies cause greater attenuation, requiring smaller RIS.

AI/ML enhances propagation and channel modeling.

Abstract

The reconfigurable intelligent surface (RIS) technology is a potential solution to enhance network capacity and coverage without significant investment in additional infrastructure in 6G networks. This work highlights the interest of the mobile communication industry in RIS, and discusses the development of liquid crystal-based RIS for improved energy efficiency and coverage in the millimeter-wave band. Furthermore, the paper discusses perspectives and insights from an industry R&D point of view, addressing relevant use cases, technical requirements, implementation challenges, and practical considerations for RIS deployment optimization in the context of 6G networks. A hardware design of an RIS with liquid crystal at 28 GHz is presented. A propagation model for RIS as a new part of the system architecture is discussed, with approaches of semi-empirical models, geometric models, and their combination through the application of artificial intelligence/machine learning. Finally, a channel model for deployment optimization and dimensioning is presented, with the findings that a rather large RIS is favorable for coverage improvement, as well as greater attenuation at higher frequencies combined with a smaller RIS size.