[Paper Review] Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How it Works, State of Research, and Road Ahead

Marco Di Renzo, Alessio Zappone+5 more|arXiv (Cornell University)|Apr 20, 2020

Advanced Wireless Communication Technologies307 references3,052 citations

TL;DR

This paper introduces reconfigurable intelligent surfaces (RIS) as a transformative technology for smart radio environments (SREs), enabling dynamic control of wireless propagation by programmatically manipulating electromagnetic waves. It unifies communication theory with electromagnetism, proposes physics-based RIS modeling, and identifies key research challenges for 6G networks.

ABSTRACT

Reconfigurable intelligent surfaces (RISs) are an emerging transmission technology for application to wireless communications. RISs can be realized in different ways, which include (i) large arrays of inexpensive antennas that are usually spaced half of the wavelength apart; and (ii) metamaterial-based planar or conformal large surfaces whose scattering elements have sizes and inter-distances much smaller than the wavelength. Compared with other transmission technologies, e.g., phased arrays, multi-antenna transmitters, and relays, RISs require the largest number of scattering elements, but each of them needs to be backed by the fewest and least costly components. Also, no power amplifiers are usually needed. For these reasons, RISs constitute a promising software-defined architecture that can be realized at reduced cost, size, weight, and power (C-SWaP design), and are regarded as an enabling technology for realizing the emerging concept of smart radio environments (SREs). In this paper, we (i) introduce the emerging research field of RIS-empowered SREs; (ii) overview the most suitable applications of RISs in wireless networks; (iii) present an electromagnetic-based communication-theoretic framework for analyzing and optimizing metamaterial-based RISs; (iv) provide a comprehensive overview of the current state of research; and (v) discuss the most important research issues to tackle. Owing to the interdisciplinary essence of RIS-empowered SREs, finally, we put forth the need of reconciling and reuniting C. E. Shannon’s mathematical theory of communication with G. Green’s and J. C. Maxwell’s mathematical theories of electromagnetism for appropriately modeling, analyzing, optimizing, and deploying future wireless networks empowered by RISs.

Motivation & Objective

• To establish the foundational principles of smart radio environments (SREs) empowered by reconfigurable intelligent surfaces (RIS) as a paradigm shift from traditional wireless networks.
• To bridge the gap between C.E. Shannon’s mathematical theory of communication and the mathematical theories of electromagnetism by G. Green and J.C. Maxwell.
• To provide physics-based models for metasurfaces and RISs that accurately describe their wave manipulation capabilities in wireless systems.
• To survey the current state of research on RIS-empowered SREs and identify critical open challenges for future development.
• To offer practical guidelines for integrating RISs into wireless networks through analytical and computational modeling techniques.

Proposed method

• Proposes a unified framework that integrates communication-theoretic models with electromagnetic wave theory to model RIS behavior in wireless channels.
• Introduces the concept of RIS as a thin, programmable surface capable of reconfiguring the reflection or transmission of radio waves via external control signals.
• Employs generalized laws of reflection and refraction derived from metasurface theory to model wavefront shaping in both far-field and near-field regimes.
• Utilizes ray tracing and system-level simulators enhanced with metasurface scattering models to evaluate performance in realistic urban and indoor environments.
• Analyzes RIS deployment in large-scale networks using stochastic geometry and stochastic geometry-based models to assess coverage and energy efficiency.
• Explores beyond-communication applications such as high-precision radio localization and mapping using the focusing capabilities of electrically large RISs.

Experimental results

Research questions

• RQ1 How can the wireless propagation environment be transformed from a passive, uncontrollable medium into a programmable, intelligent surface?
• RQ2 What are the fundamental physical principles governing the operation of reconfigurable intelligent surfaces (RISs) and how can they be mathematically modeled?
• RQ3 How can Shannon’s information theory be reconciled with Maxwell’s electromagnetism to enable intelligent radio wave control?
• RQ4 What are the performance gains and limitations of RIS-empowered smart radio environments in real-world, large-scale deployments?
• RQ5 What are the key challenges in enabling RISs for near-field communications, localization, and system-level integration?

Key findings

• RISs can significantly enhance spectral and energy efficiency by dynamically controlling radio wave propagation, reducing interference, and improving signal reliability.
• The integration of metasurfaces into wireless networks enables new capabilities such as beamforming, wavefront shaping, and intelligent multipath exploitation.
• Current system-level simulators lack support for metasurface scattering models, creating a critical gap in performance evaluation and deployment planning.
• Near-field operation of large RISs offers new opportunities for high-gain focusing and precision localization, but remains underexplored in existing literature.
• Large-scale deployment of RISs requires new analytical frameworks to determine optimal density and placement for coverage and energy efficiency in urban and industrial environments.
• Beyond communications, RISs show promise for radio mapping and localization, suggesting a broader role in intelligent wireless environments.