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Reconfigurable Intelligent Surfaces for 6G: Emerging Hardware Architectures, Applications, and Open Challenges

Ertugrul Basar, George C. Alexandropoulos, Yuanwei Liu, Qingqing Wu, Shi Jin, Chau Yuen, Octavia A. Dobre, Robert Schober

arXiv:2312.16874v2cs.ITeess.SP

TL;DR

RIS research needs a unified view of hardware architectures and their operating modes for emerging 5G-Advanced and 6G connectivity. This article synthesizes architectures, applications, experiments, and open challenges, reporting both a 25% bit-rate increase in RIS-based IM-MIMO-QAM and a 4.03 dB field-trial gain in received signal power.

  • Problem

    The paper addresses the need to understand RIS hardware architectures, operating modes, applications, and open challenges for emerging 5G-Advanced and 6G wireless networks.

  • Method

    The article surveys RIS architectures and applications, reviews prototypes and field trials, and discusses open problems across the technology.

  • Results

    25% bit rate increase was reported for RIS-based 2×2 IM-MIMO-QAM over an RIS-aided single-antenna 16-QAM system, while a field trial measured a 4.03 dB received-signal-power gain over a benchmark without the metasurface.

  • Takeaways & Limitations

    RISs provide a broad platform for propagation control, new communication and sensing modes, and applications including reflection modulation, NGMA, ISAC, and EH.

Abstract

from arXiv · show

Reconfigurable intelligent surfaces (RISs) are rapidly gaining prominence in the realm of fifth generation (5G)-Advanced, and predominantly, sixth generation (6G) mobile networks, offering a revolutionary approach to optimizing wireless communications. This article delves into the intricate world of the RIS technology, exploring its diverse hardware architectures and the resulting versatile operating modes. These include RISs with signal reception and processing units, sensors, amplification units, transmissive capability, multiple stacked components, and dynamic metasurface antennas. Furthermore, we shed light on emerging RIS applications, such as index and reflection modulation, non-coherent modulation, next generation multiple access, integrated sensing and communications (ISAC), energy harvesting, as well as aerial and vehicular networks. These exciting applications are set to transform the way we will wirelessly connect in the upcoming era of 6G. Finally, we review recent experimental RIS setups and present various open problems of the overviewed RIS hardware architectures and their applications. From enhancing network coverage to enabling new communication paradigms, RIS-empowered connectivity is poised to play a pivotal role in shaping the future of wireless networking. This article unveils the underlying principles and potential impacts of RISs, focusing on cutting-edge developments of this physical-layer smart connectivity technology.

I. INTRODUCTION

The article surveys RIS hardware architectures, operating modes, applications, prototypes, field trials, and open challenges as 5G-Advanced and 6G networks develop.

  • RISs manipulate the radio propagation environment to support wireless connectivity in emerging 5G-Advanced and 6G networks.
  • Hardware architectures: The article covers architectures with reception and processing units, sensors, amplification, transmissive capability, stacked components, and dynamic metasurface antennas.
  • Operating modes: These architectures produce operating modes supporting network coverage, communication paradigms, and sensing through real-time wireless-environment adaptation.
  • Applications: Emerging applications include reflection, index, and non-coherent modulation, NGMA, EH, ISAC, and aerial and vehicular networks.
  • Evidence and challenges: The article reviews real-world RIS prototypes, a commercial-5G field trial, and open problems and challenges.
  • Foundations: RISs comprise controllable meta-atoms that manipulate impinging electromagnetic waves, with a controller retaining or changing their states.

A. Metasurface-Based Hardware Architectures

RIS hardware architectures trade propagation control, signal strength, energy use, cost, channel knowledge, and sensing capability across passive, active, optical, and receiving designs.

  • Reflection amplifiers: RISs act as groups of scatterers, so passive systems experience double path loss from the transmitter–RIS and RIS–receiver links.The resulting multiplicative loss reduces effectiveness when the RIS is far from communicating terminals.
  • Reflection amplifiers: Active RISs amplify outgoing RF signals without a transceiver RF chain or signal processing, converting multiplicative path loss into additive path loss.Their higher energy consumption must be weighed against the amplification benefit.
  • FSO integration: RIS-assisted FSO links can redirect blocked line-of-sight signals but introduce increased attenuation and double fading over the two channel portions.
  • Channel knowledge: Passive RIS operation commonly requires channel knowledge obtained through substantial receiver-side estimation overhead and sharing with the RIS controller.
  • Signal reception: Receiving RISs add reception RF chains containing amplification, downconversion, and analog-to-digital conversion to estimate impinging-signal parameters for optimization.A multi-element RIS can reconstruct such parameters using a single RF chain with random spatial sampling and compressed sensing.

3) RISs with Signal Reception and Reflection Units:

RISs with reception and reflection units combine environmental wave manipulation with sensing, while related metasurface architectures extend operation toward antennas, stacked 3D devices, and wave-domain processing.

  • Reception and reflection: Receiving-and-reflecting RISs either combine conventional reflective meta-atoms with sensing devices or use hybrid meta-atoms that split incident power between reflection and reception.
  • Reception and reflection: In hybrid RISs, the reflected-to-sensed energy ratio is controlled by meta-atom coupling to waveguides, so incident waves are not perfectly reflected.
  • Dynamic metasurface antennas: Dynamic metasurface antennas use reconfigurable meta-atoms as transmit and receive antennas to control analog transmission and reception beampatterns.
  • Stacked intelligent metasurfaces: Stacking RIS arrays creates three-dimensional SIM devices in which each layer’s meta-atoms act as secondary sources illuminating subsequent layers.

5) Stacked Intelligent Metasurfaces (SIM):

Stacked intelligent metasurfaces (SIMs) use multiple transmissive RIS layers to manipulate electromagnetic waves hierarchically and perform analog processing in the propagation domain. Their applications include holographic MIMO, where increasing layer counts make the end-to-end channel matrix closer to diagonal.

  • Stacked Intelligent Metasurfaces (SIM): SIMs stack RIS layers into a three-dimensional slab whose tunable meta-atoms hierarchically manipulate transmitted electromagnetic-wave energy.Each layer’s meta-atoms receive superimposed waves from preceding layers and act as reprogrammable processing elements.
  • Stacked Intelligent Metasurfaces (SIM): SIMs can execute signal-processing and computation tasks directly in the electromagnetic-wave domain, with forward propagation occurring at the speed of light.The architecture is analogous to an artificial neural network, with electronically tunable meta-atoms functioning as reprogrammable artificial neurons.
  • Holographic MIMO: A holographic MIMO transceiver places SIMs near the transmitter and receiver to perform analog precoding and combining in the electromagnetic domain.The design combines this analog processing with lower-resolution DACs at the transmitter and ADCs at the receiver.
  • Holographic MIMO: As the numbers of metasurface layers K and L increase, the end-to-end channel matrix becomes closer to diagonal.This supports more separable channel processing in the SIM-based holographic MIMO architecture.
  • STAR-RIS: STAR-RISs combine transmission and reflection, eliminating the same-side transmitter–receiver requirement and enabling 360◦ full-space coverage.This supports deployments on walls between separated spaces and on windows for indoor–outdoor communication.
  • STAR-RIS: STAR-RIS meta-atoms require tunable electrical and magnetic responses, while independent transmitted and reflected phase shifts can require lossy or active elements with higher hardware cost.Metasurface-based implementations may offer transparency to visible light and compatibility with high-frequency communications.

B. Operation Modes

RIS hardware architectures support operating capabilities beyond passive wave steering, including sensing and signal processing. Hybrid RISs can estimate channels using sensed pilot observations, while RICS architectures add computation and control layers.

  • Operation capabilities: Metasurface-based RIS architectures can provide wave steering, polarizing, absorbing, filtering, and collimation beyond passive RIS operation.
  • Sensing and processing: Sensors-embedded passive RISs and hybrid RISs can estimate parameters of impinging signals at the metasurface side.The signal-processing capability is selected according to cost, power, and size constraints.
  • Reconfigurable intelligent computational surfaces: RICS architectures combine a reconfigurable beamforming layer, an intelligence computation layer, and a controller-connected control layer.The layers support tunable reflection, absorption, refraction, task-oriented computation, and parameter configuration.
  • Sensing and processing: Hybrid RISs can estimate individual user channels from sensed pilot observations and forward the estimates to a base station over an out-of-band control link.The metasurface changes its phase configuration across orthogonal pilot-symbol transmissions.
  • STAR-RIS operating modes: STAR-RISs operate through energy splitting, mode switching, or time switching, trading implementation flexibility against complexity and synchronization requirements.Energy splitting transmits and reflects simultaneously; mode switching assigns each meta-atom to one function; time switching alternates functions across slots.

2) 360◦Signal Coverage:

RICS designs combine reconfigurable beamforming with task-oriented computation through distinct reflection-absorption or reflection-refraction modes. These configurations determine whether computation uses neuromorphic or analog processing.

  • RICS designs: The two RICS designs configure the same beamforming and computation layers differently to meet various computational tasks.
  • Design A: RICS Design A combines reflection-absorption beamforming with neuromorphic computing.Its beamforming layer uses passive reflecting meta-atoms and semi-active elements connected to a few receiver RF chains for incident-signal processing.
  • Design A: In Design A, the neuromorphic-computing layer can use nanoribbons whose light scattering implements an equivalent computational operation.
  • Design B: RICS Design B combines reflection-refraction beamforming with analog computing.The incident energy is divided between reflection and refraction, and the refracted signal is processed to perform mathematical operations.
  • Design B: Reflection-refraction mode enables computation on a refracted signal while retaining a reflected component of the incident energy.

III. RIS-INSPIRED WIRELESS APPLICATIONS

RISs support emerging wireless applications that encode information through indices or programmable reflections, while RICSs extend these ideas to spectrum learning and secure transmission. The surveyed applications also include non-coherent modulation and RIS-induced data embedding over OFDM signals.

  • Application overview: RIS-empowered index modulation and reflection modulation use metasurface flexibility to create new transmission formats.
  • Index Modulation (IM): Index modulation conveys binary information through selected transmit entities such as antennas, subcarriers, antenna patterns, or spreading codes.RISs add a spatial dimension through transmit-side or receive-side activation designs.
  • Reflection Modulation: Reflection modulation remodulates an incident unmodulated or modulated signal by adjusting RIS reflection coefficients.An unmodulated carrier can be transformed into a virtual phase-shift-keying constellation at the receiver.
  • RICS applications: RICS application designs include wireless spectrum learning and secure data transmissions.
  • Reflection Modulation: Reflection modulation can embed RIS-generated bits independently or coordinate reflection patterns jointly with transmitter bits.
  • Non-coherent modulation: RIS-based modulation designs include virtual space–time coding, space-shift keying, and non-coherent detection based on received-signal power and component polarities.
  • OFDM and RIS-induced data: RIS modulation must support OFDM, including frequency-modulating RISs that generate multi-subcarrier signals and low-rate RIS-induced streams embedded over impinging OFDM signals.

B. Non-Coherent Modulation

Non-coherent RIS communications address the impractical overhead of accurate channel estimation by avoiding pilot-dependent CSI acquisition. The section reviews differential, secure, and zero-overhead beam-training designs, alongside RIS-enabled multiple-access schemes.

  • Motivation: Perfect CSI is impractical because rapidly varying channels, nearly passive RIS designs, and pilot transmission create substantial estimation overhead.Non-coherent communications avoid the need for transmitting pilots for channel estimation.
  • Non-coherent RIS designs: RIS-JIK-MDCSK jointly optimizes reference-signal, RIS-element, and information-subcarrier states to form a non-coherent index-keying mechanism.The design targets excessive overhead caused by channel estimation in coherent RIS-aided systems.
  • Non-coherent RIS designs: A chaotic secure RIS communication system uses block interleaving and sequential or joint detection to recover information bits without relying on signal similarity.Sequential detection uses energy detection with lower complexity, whereas joint detection performs joint recovery.
  • Beam training: Zero-overhead RIS beam training uses non-coherent demodulation and received differential data to select the best reflection phase profile.Simulations reported that non-coherent modulation remains suitable in high-mobility scenarios.
  • Next-generation multiple access: RISs provide additional degrees of freedom for enhancing existing multiple-access schemes and enabling new schemes such as holographic-pattern division multiple access.An RIS transceiver can generate multiple superimposed holographic patterns, while extremely large surfaces can exploit near-field effects.

D. Integrated Sensing and Communications (ISAC)

RISs support integrated sensing and communications by engineering additional propagation paths and jointly shaping sensing and communication subspaces. These capabilities extend localization and sensing to non-line-of-sight and infrastructure-limited environments.

  • ISAC foundations: 5G positioning signals, wider bandwidths, and large antenna arrays improve localization, while ISAC reuses frequency bands for communications and sensing.ISAC targets passive-object detection and tracking applications including gesture capturing and activity recognition.
  • Joint sensing and communications: An RIS can be optimized to expand and rotate sensing and communications subspaces, maximizing collective gains from simultaneous operations.The design jointly shapes the two subspaces rather than treating sensing and communications as independent functions.
  • RIS-enabled sensing: RISs create additional signal-path diversity and virtual line-of-sight conditions for RF localization, sensing, and ISAC.These engineered paths can support services in non-line-of-sight environments and scenarios with few transmitting terminals.
  • RIS-enabled sensing: RIS-aided sensing has been studied for environmental mapping, non-line-of-sight millimeter-wave and terahertz sensing, and monostatic or bistatic radar.Metasurfaces can optimize illuminated power in target geographical areas to improve passive- and active-target identification.

E. Energy Harvesting

RISs improve RF energy harvesting by focusing reflected beams, extending wireless power coverage, and bypassing blockages. Their integration with SWIPT and WPCNs introduces throughput and energy-consumption benefits, while active RISs trade amplified noise and power consumption for stronger received power and range.

  • Motivation: RF energy harvesting suffers low energy efficiency over long distances because wireless-channel impairments reduce received power.Increasing transmitter radiation power does not improve end-to-end efficiency by itself.
  • RIS-assisted energy harvesting: Fine-grained RIS reflections compensate long-distance attenuation, create enhanced charging zones, and establish virtual line-of-sight links around blockages.These mechanisms can enlarge wireless power-transfer coverage and improve energy-harvesting performance.
  • System paradigms: RISs integrate with the two main RF energy-harvesting paradigms: simultaneous wireless information and power transfer and wireless-powered communication networks.SWIPT uses the same RF signals for simultaneous information transmission and wireless power transfer.
  • System paradigms: RIS-aided WPCNs enhance system throughput while simultaneously reducing access-point energy consumption.This twofold advantage is explicitly reported for the WPCN setting.
  • Active RISs: Active RISs can extend WPT range and improve received power by alleviating cascaded-channel product path loss, but their amplified noise is detrimental to wireless information transmission.Numerical results also report higher throughput with lower total energy consumption for active-RIS WPCNs than passive-RIS counterparts.
  • Open challenges: RIS applications in vehicular and aerial networks remain constrained by difficult real-time channel acquisition, complex interference topology, and real-time resource allocation.These issues remain unresolved when the two network types are integrated.

IV. RIS PROTOTYPES AND FIELD TRIALS

Recent RIS prototypes span industrial, academic, and collaborative research efforts, including experimental systems for index modulation and cellular coverage extension. A demonstrated 2 × 2 IM-MIMO-QAM prototype shows measurable bit-rate and SNR benefits when constellation compensation is used.

  • Experimental landscape: Experimental RIS research has expanded through prototypes from industrial and academic organizations and multi-partner projects such as RISE-6G.The surveyed organizations include ZTE, Huawei, NEC Laboratories, and several universities.
  • Experimental focus: The reviewed prototype section focuses on RIS-based index-modulation prototyping and RIS-empowered coverage extension for commercial 5G cellular networks.These are identified as two emerging RIS application areas for experimental study.
  • IM-MIMO-QAM prototype: The RIS-based 2 × 2 IM-MIMO-QAM prototype operates with a 12-element RIS whose left and right subsurfaces are selected by index bits.The transmitter includes a control platform, feed antenna, and RF signal generator; the receiver uses two antennas, a USRP, and a computer.
  • Experimental results: 25% higher bit rate was achieved than an RIS-aided single-antenna 16-QAM system at the same symbol rate.The reported gain is attributed mainly to the implicit transmission dimension provided by the index bit.
  • Experimental results: About 9.5 dB lower average SNR was required than 32-QAM single-antenna transmission at a bit error rate of 10^-5.Constellation compensation restored consistency with the standard 16-QAM constellation and avoided sharp deterioration from phase deviation.

B. RIS-Based 5G Coverage Enhancement

RISs can extend 5G coverage by flexibly regulating incident signals, while field trials and open challenges highlight both practical gains and deployment constraints.

  • RISs regulate incident signals with low cost and are considered a potential technology for extending coverage.
  • A commercial 5G field trial used a closed-loop phase-configuration algorithm to optimize RIS reflective beamforming.
  • The trial placed the RIS to create line-of-sight paths to both the base station and test terminal while trees blocked their direct path.
  • 4.03 dB gain in received signal power was measured over the benchmark without the metasurface.
  • Open challenges: Active and hybrid RIS designs must trade power consumption and implementation cost against illumination area, energy efficiency, and application scenarios.
  • Open challenges: Reflection-modulation designs face limited data rates, while RIS-assisted energy harvesting and aerial or vehicular networks face mobility and placement challenges.
  • Open challenges: Standalone smart RISs and efficient placement remain open requirements for reducing control-signaling overhead in real-world deployments.

VI. CONCLUSIONS

The article synthesizes RIS hardware architectures, operating modes, applications, and design challenges for 6G wireless communications and sensing. It presents RISs as a technology with broad capabilities and potential future roles in connected systems.

  • The article covers RIS architectures, operating modes, applications including reflection modulation, NGMA, ISAC, and EH, and associated design challenges.
  • The review provides insights into the capabilities and potential challenges of RIS-enabled smart wireless environments.
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