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Intelligent Surfaces Empowered Wireless Network: Recent Advances and The Road to 6G

Qingqing Wu, Beixiong Zheng, Changsheng You, Lipeng Zhu, Kaiming Shen, Xiaodan Shao, Weidong Mei, Boya Di, Hongliang Zhang, Ertugrul Basar, Lingyang Song, Marco Di Renzo, Zhi-Quan Luo, Rui Zhang

arXiv:2312.16918v3cs.ITeess.SP

TL;DR

Wireless-network research on ISs is advancing across architectures, applications, and design methods, motivating a timely synthesis. This paper surveys those developments, reporting improved blind beamforming scaling with CSM and identifying open practical issues.

  • Problem

    IS research spans passive reflection, active amplification, integrated active/passive surfaces, sensing, and advanced electromagnetic architectures, but remains rapidly evolving.

  • Method

    The paper synthesizes applications, standardization, reflection-based design issues, advanced IS architectures, recent solutions, and future research challenges.

  • Results

    CSM yields SNR ∝N^2 for polynomially large T and approximately 8 dB higher SNR than RMS at N = 256, K = 2, and T = 10N.

  • Takeaways & Limitations

    The survey maps a transition toward cooperative, active, refractive, aerial, mobile, and multifunctional ISs while framing their unresolved design issues.

  • Takeaways & Limitations

    Practical deployment and design remain constrained by challenging CSI acquisition, non-implementable ideal coefficients, and slow hardware response in some IS implementations.

Abstract

from arXiv · show

Intelligent surfaces (ISs) have emerged as a key technology to empower a wide range of appealing applications for wireless networks, due to their low cost, high energy efficiency, flexibility of deployment and capability of constructing favorable wireless channels/radio environments. Moreover, the recent advent of several new IS architectures further expanded their electromagnetic functionalities from passive reflection to active amplification, simultaneous reflection and refraction, as well as holographic beamforming. However, the research on ISs is still in rapid progress and there have been recent technological advances in ISs and their emerging applications that are worthy of a timely review. Thus, we provide in this paper a comprehensive survey on the recent development and advances of ISs aided wireless networks. Specifically, we start with an overview on the anticipated use cases of ISs in future wireless networks such as 6G, followed by a summary of the recent standardization activities related to ISs. Then, the main design issues of the commonly adopted reflection-based IS and their state-of-the-art solutions are presented in detail, including reflection optimization, deployment, signal modulation, wireless sensing, and integrated sensing and communications. Finally, recent progress and new challenges in advanced IS architectures are discussed to inspire futrue research.

I. INTRODUCTION

The paper introduces ISs as a technology for future wireless networks, including 6G, and outlines their evolving architectures and classifications.

  • A. Overview of 6G: 6G usage scenarios include immersive, massive, and hyper-reliable low-latency communications, alongside newly introduced scenarios.Immersive communication can require 10 Gbps user-experienced data rates and 1 Tbps peak data rates, while massive communication targets 10^6–10^8 devices/km^2.
  • 1) Historical Development of ISs: IS research evolved from reflectarrays and metamaterials toward programmable surfaces for wireless sensing and communications.The historical development includes reflectarrays, metamaterials, programmable metamaterials, and later intelligent-surface concepts.
  • 2) Classifications of ISs: ISs encompass continuous or discrete surfaces, with discrete ISs using separated elements and continuous ISs using a continuous aperture.The classification distinguishes the physical aperture structure of the surface.
  • 2) Classifications of ISs: ISs may be reflection-based, refraction-based, or simultaneously reflective and refractive to provide full-space coverage.The classification includes completely reflected, completely refracted, and partially reflected-and-refracted signals.
  • 2) Classifications of ISs: Passive ISs manipulate incident signals without amplification, whereas active ISs amplify them while controlling phase shifts.The paper uses passive to denote ISs without power-amplification capability.

3) Applications of ISs in 6G:

ISs are envisioned for diverse 6G applications, and related standardization efforts address their integration into future wireless systems.

  • 3) Applications of ISs in 6G: ISs can support immersive and hyper-reliable low-latency applications by overcoming path loss, bypassing obstacles, and providing additional propagation paths.Examples include extended reality, ultra-high-definition video, industrial control, smart health, and smart transportation.
  • 3) Applications of ISs in 6G: ISs can improve wireless data aggregation, distributed computing, monitoring, and control in integrated AI and communication scenarios.The paper specifically discusses edge AI applications such as federated learning.
  • 3) Applications of ISs in 6G: ISs can serve as additional reference nodes in ISAC to enhance positioning, sensing, and communication performance.Potential services include navigation, high-precision positioning, user activity detection, and tracking.
  • 3) Applications of ISs in 6G: IS usefulness has been demonstrated experimentally across sub-6 GHz, mmWave, THz, and optical frequency bands.Representative prototypes and field trials are summarized in Table I.
  • 3) Applications of ISs in 6G: ISs have been included in the ITU-R IMT-2030 future-technology report and are under evaluation by standardization bodies.The paper places IS standardization alongside related work on THz communications and ISAC.
  • 1) Third Generation Partnership Program (3GPP): 3GPP Rel-18 proposals address IS use cases, deployment, channel modeling, beam management, control interfaces, interference coordination, and related repeater support.The proposals include studies of ISs, NR repeaters, smart repeaters, and compatibility with legacy user equipment.
  • 1) Third Generation Partnership Program (3GPP): Network-controlled repeaters are considered a stepping stone for ISs because their control channel may be reused.NCRs aim to reduce noise amplification and support improved spatial directivity.

2) European Telecommunication Standards Institute (ETSI):

ETSI provides an open, consensus-based setting for early standardization, while ISG-IS organizes IS-related work across use cases, architectures, models, implementation, air interfaces, and multifunctionality.

  • 2) European Telecommunication Standards Institute (ETSI): ETSI develops ICT standards, specifications, reports, and guides through member participation and contribution-driven consensus.Its industry specification groups support early standardization arising from fundamental and applied research.
  • 2) European Telecommunication Standards Institute (ETSI): ETSI launched ISG-IS in September 2021 to review and establish global standardization activities for IS technology.Its scope includes use cases, radio-frequency aspects, air interfaces, control signaling, architecture, evaluation, and enabling technologies.
  • 2) European Telecommunication Standards Institute (ETSI): IS verification and validation is identified as an additional standardization activity.
  • 2) European Telecommunication Standards Institute (ETSI): A further work item targets multifunctional IS modeling, optimization, and operation across transmission, reflection, sensing, computation, deployment, and resource allocation.The second phase is tailored toward an initial specification framework for the technology.

D. Aims and Organization

The paper surveys recent IS advances, covering reflection-based designs and advanced architectures while identifying unresolved issues for future research.

  • D. Aims and Organization: The survey aims to provide a comprehensive overview of recent IS development, emphasizing research results, new architectures, and associated design issues.It distinguishes its scope from existing overview, survey, tutorial papers, and books.
  • D. Aims and Organization: The paper is organized into reflection-based ISs, advanced IS architectures, and a concluding section.Section II covers reflection-based IS design, Section III covers advanced architectures, and Section IV concludes the paper.
  • D. Aims and Organization: Advanced IS architectures and their new design issues and solutions are discussed separately from reflection-based IS design.
  • D. Aims and Organization: Reflection-based IS coverage includes reflection optimization, deployment, signal modulation, wireless sensing, and ISAC.
  • D. Aims and Organization: The paper highlights unresolved problems to motivate future IS research and development for applications in future wireless networks such as 6G.

II. REFLECTION-BASED IS: DESIGN ISSUES AND STATE-OF-THE-ART RESULTS

Reflection-based IS design centers on configuring element reflection coefficients, with recent methods reducing reliance on explicit channel estimation and improving practical beamforming efficiency. Blind, channel-recovery, and beam-training approaches trade off measurement requirements, search complexity, and performance, while CSM achieves quadratic SNR scaling with polynomially many samples.

  • Reflection optimization: Reflection optimization configures all IS-element coefficients using estimated cascaded BS-IS-user channels in most existing two-stage methods.The channel is estimated from downlink/uplink pilots before reflection coefficients are optimized.
  • Power-measurement-based design: Received-power measurements enable practical IS reflection design using accessible user-terminal measurements such as RSRP.These approaches avoid relying directly on baseband complex-valued pilots.
  • Power-measurement-based design: Blind design optimizes each RE phase from power measurements without explicit CSI, whereas channel recovery first estimates the cascaded channel before optimization.Beam training instead selects a directional beam from a predefined codebook, particularly exploiting channel sparsity at mmWave frequencies.
  • Blind reflection/beamforming: RMS samples random phase configurations and retains the best observed performance, but exhaustive search becomes intractable as real-world ISs contain many REs.A prototype with 256 REs already makes the solution space difficult to search exhaustively.
  • Blind reflection/beamforming: SNR ∝N log N for RMS with polynomially many samples, whereas CSM achieves SNR ∝N^2 under the same sample-growth regime.In 2.6 GHz 5G field tests with N = 256, K = 2, and T = 10N, CSM was approximately 8 dB higher than RMS.

2) Channel Recovery-Based Reflection/Beamforming:

IS reflection and beamforming can be designed either without explicit CSI from power measurements or through channel recovery, while beam training adapts codebooks and procedures to frequency and field conditions.

  • Channel Recovery-Based Reflection/Beamforming: Blind designs use random phase-shift samples and received-power measurements, whereas channel recovery exploits power constraints to estimate the cascaded channel.Lifting channel vectors into autocorrelation matrices makes the otherwise non-convex power constraints linear.
  • Channel Recovery-Based Reflection/Beamforming: SDP-based beamforming needs the fewest power measurements but has the highest computational complexity; RMS has the lowest complexity but performs poorly with few measurements.CSM and NN-based methods provide an intermediate trade-off between measurement requirements, complexity, and effective channel gain.
  • Beam Training: At mmWave and higher frequencies, directional codebook-based training avoids explicit CSI estimation, but beam training must trade passive beamforming gain against training overhead.Far-field procedures can align the fixed BS–IS link offline and select the best IS codeword online; wideband systems additionally face beam squint.
  • Beam Training: Near-field XL-IS training requires specialized Cartesian or polar codebooks, while two-phase designs reduce the large training-symbol cost of exhaustive codeword search.The underlying overhead remains challenging because the two-phase XL-IS scheme is proportional to the number of IS REs.
  • Channel Recovery-Based Reflection/Beamforming: For sub-6 GHz systems, both approaches can support real-time reflection design under slow fading, while statistical or deterministic channel components extend feasibility to fast-fading channels.Wide IS beams based on statistical channel knowledge or deterministic components can improve long-term coverage over a target region.

B. Deployment

IS deployment strongly affects reflected channels and communication performance, motivating practical deployment strategies tailored to different use cases.

  • B. Deployment: IS placement has a significant impact on reflected channels and the performance of IS-aided communication systems.The section compares practical deployment approaches according to their performance advantages in different use cases.
  • B. Deployment: Deployment strategies should therefore be evaluated in relation to the intended communication use case.The passage frames deployment as a design problem rather than a fixed placement choice.
  • B. Deployment: Practical IS deployment approaches are compared through their performance advantages across different use cases.The comparison is motivated by the deployment-dependent behavior of reflected channels.

1) BS-Side IS:

BS-side, integrated, and distributed multi-IS architectures address deployment cost, path loss, coverage, and signaling challenges, but introduce channel-estimation or deployment-design difficulties.

  • 1) BS-Side IS: User-side IS deployment may require dense placement for random users, while nearby ISs mainly provide passive beamforming because distant reflections suffer greater path loss.This motivates placing ISs near or at the BS to assist distributed users.
  • 1) BS-Side IS: Co-site ISs assist distributed users regardless of location, while IS-integrated BSs further reduce product-distance path loss through shorter IS–antenna separation.Closely spaced elements with different orientations can also provide multiple reflections and improve path diversity and effective channel gain.
  • 1) BS-Side IS: BS-integrated ISs can reduce signaling overhead and provide power supply, but their near-field and multi-reflection channels make channel estimation more challenging.Random-phase and codebook-based passive designs are proposed to avoid or reduce reliance on explicit CSI and extensive online measurements.
  • 2) Multi-IS Deployment: BS-side reflections alone may not bypass dense obstacles, motivating multiple distributed ISs that create additional cascaded LoS paths for coverage enhancement.Multi-IS deployment therefore requires selecting locations that suit the practical environment.
  • 2) Multi-IS Deployment: Graph-based deployment models divide coverage into cells and candidate locations, then characterize LoS availability, deployment cost, and communication performance.Enhanced models evaluate SNR at user locations rather than relying only on the number of reflections.
  • 2) Multi-IS Deployment: Integrating active ISs can reduce total deployment cost for a target SNR by reducing the number of passive ISs required, although multi-IS performance modeling remains important.Earlier evaluation based only on reflections per link may not accurately represent each user's actual performance.
  • 3) Relay-side ISs: IS-integrated relays actively relay information without additional deployment or hardware cost and can improve effective gain, path diversity, coverage range, and signaling efficiency.Their shorter IS–relay distance contributes to reduced product-distance path loss.
  • 3) Relay-side ISs: Full-duplex IS-integrated relaying could enable one-phase transmission but introduces self-interference and requires balancing the BS–relay and relay–user links.Half-duplex operation is considered easier to implement but requires two-phase relaying transmission.

4) Aerial ISs:

Aerial ISs extend intelligent-surface deployment into UAV, balloon, and satellite platforms, while high-mobility settings motivate roadside and vehicle-side alternatives. These deployments improve coverage and channel reliability but retain practical challenges in channel acquisition, mobility, interference, and hardware imperfections.

  • 4) Aerial ISs:: Aerial ISs mounted on UAVs or balloons provide additional LoS air-to-ground or air-to-air links for signal enhancement, especially in post-disaster or scarcely covered areas.Their placement and 3D passive beamforming can be jointly optimized.
  • 4) Aerial ISs:: LEO satellite communications are an emerging aerial application in which ISs can mitigate Doppler effects and improve satellite-terrestrial and inter-satellite links.Two-sided cooperative ISs can support distributed channel estimation and beam tracking.
  • 5) Roadside and Vehicle-side ISs:: High-mobility communications challenge static-channel IS designs because rapidly varying Doppler-induced phases produce superimposed multipath fast fading.Real-time reflection or refraction control can convert fast fading to slow fading for more reliable communications.
  • 5) Roadside and Vehicle-side ISs:: Vehicle-side IS deployment uses one IS per vehicle, enabling persistent association with onboard users and less frequent IS-BS handover than roadside deployment.Both roadside and vehicle-side ISs may use reflection or refraction depending on deployment conditions.
  • Deployment strategies: The reviewed deployment strategies span BS-side, cooperative, relay-side, aerial, roadside, and vehicle-side ISs, supporting adaptation to diverse wireless environments and application scenarios.Future practical work must address cross-band interference, hardware imperfections, and costly channel estimation.

2) IS for Index Modulation:

Transmitter-type ISs participate directly in signaling and modulation, supporting index modulation alongside other schemes and enabling virtual transmission architectures. The section also situates IS sensing architectures and their hardware trade-offs within IS-aided wireless systems.

  • 2) IS for Index Modulation:: Index modulation encodes information through the indices of available transmit entities, motivating transmitter-type IS systems illuminated by an unmodulated carrier.IS-based index modulation can be applied at different parts of the system.
  • 2) IS for Index Modulation:: Jointly mapped and separately mapped index modulation differ in whether transmitter and IS data are mapped jointly or independently.A discrete optimization-based design can jointly map, shape, and reflect signals for improved transmission reliability.
  • 2) IS for Index Modulation:: Transmitter-type ISs simplify hardware and enhance signal quality through signaling and modulation, including PSK, QAM, FSK, and virtual MIMO transmission diversity.Their operation can be based on amplitude-phase modulation or index modulation.
  • IS-aided sensing: IS-aided sensing architectures include passive, semi-passive, active, and target-mounted designs with different performance, hardware-cost, and implementation-complexity trade-offs.Semi-passive sensing adds low-cost active sensors to receive target echoes directly, reducing cascaded path loss relative to passive sensing.
  • IS-aided sensing: Target-mounted ISs can improve sensing accuracy and support secure sensing by enhancing legitimate-radar performance while preventing unauthorized target detection.The secure-sensing protocol uses a target-mounted semi-passive IS and divides each radar coherent-processing interval into two phases.

2) IS-aided ISAC:

IS-aided ISAC combines sensing and communication while addressing sensing-range and protocol-integration challenges in cellular UAV and mmWave systems. The reviewed approaches expose trade-offs between communication rate, sensing accuracy, beam-training time, and hardware complexity.

  • 2) IS-aided ISAC:: Cellular UAV ISAC must achieve sensing and communication performance without significantly changing existing cellular protocols.Cooperative IS beam searching and BS communication signals are used for UAV target sensing.
  • 2) IS-aided ISAC:: The cellular UAV sensing protocol estimates the background channel, then sequentially estimates UAV angle parameters using cooperative IS beam states.Idle BSs and sensing resource blocks can be selected to support the procedure.
  • 2) IS-aided ISAC:: MmWave ISAC uses ISs to compensate for high path loss, improving sensing coverage and communication performance while exploiting beam scanning or training for target sensing.This connects communication beam management with sensing functionality.
  • 2) IS-aided ISAC:: As beam training time increases, communication achievable rate first rises and then falls, whereas sensing RCRB decreases monotonically.The reported setting uses 64 IS REs, 8 sensors, and a 28 GHz carrier frequency.
  • 2) IS-aided ISAC:: IS-aided sensing research covers passive, semi-passive, active, and target-mounted sensing, alongside cellular-UAV and mmWave ISAC systems.Future work includes connecting sensing and communication channels and exploiting target-mounted IS, STAR-RIS, and active IS architectures.

2) Integrated Active/Passive IS:

Integrated active/passive IS designs combine amplification and passive reflection either within one surface or across distributed surfaces. Their benefits are accompanied by placement, density, power, and implementability considerations, while omnidirectional designs extend coverage beyond reflection-only angular restrictions.

  • 2) Integrated Active/Passive IS:: Hybrid active/passive ISs place active and passive elements on a single surface to harness their respective advantages.This architecture is illustrated as one form of integrated active and passive IS design.
  • 2) Integrated Active/Passive IS:: Distributed integration deploys active and passive ISs separately, including networks where active ISs augment passive beam routing over multi-reflection paths.Active-IS placement can differ between wireless information transfer and wireless power transfer because amplification noise has different roles.
  • 2) Integrated Active/Passive IS:: Existing active-IS studies often assume continuous, independent phase-shift and amplitude control, which may not be implementable in practice.Further work also concerns active/passive IS density optimization and globally passive surface-wave designs.
  • Omnidirectional IS: Reflection-based ISs serve only users and BSs in the same reflection half-space, motivating omnidirectional ISs for full-space coverage.The reported omnidirectional design ensures doubled 360° service coverage compared with reflection-based IS.
  • Omnidirectional IS: Omnidirectional IS elements use electrically controllable metallic patches and PIN diodes whose ON/OFF states determine reflection and refraction responses.Reflection and transmission amplitudes can differ, with their power ratio determined by the hardware implementation.

2) New Characteristics:

Omnidirectional intelligent surfaces simultaneously reflect and refract signals, introducing coupled channel, beamforming, implementation, and optimization issues. These properties also enable applications such as full-duplex self-interference cancellation.

  • Channel Characteristics: UL and DL channels remain reciprocal, but their beams are not, so different phase configurations may be needed for transmission directions.Channel estimation remains difficult because reflection and refraction are coupled.
  • Phase Shift Optimization: Omnidirectional IS phase optimization differs from reflection-only IS design because users may lie on both sides of the surface.For known CSI, hybrid beamforming and multi-layer beam training support coverage extension and codeword selection.
  • New Characteristics: Omnidirectional ISs split incident energy between reflection and refraction, requiring coupled phase and energy-allocation designs.Implementation can use power-domain splitting or polarization-dependent control.
  • New Characteristics: BD-RIS uses coupled elements grouped into impedance-network cells or sub-surfaces, allowing broader amplitude and signal-processing optimization.An M-port sub-surface lets incident signals reach any reflective or refractive patch within that sub-surface.
  • Applications and Challenges: Omnidirectional ISs can enhance a desired signal by reflection while nulling self-interference through refraction in full-duplex systems.The coupled reflection–refraction design also complicates joint optimization and requires further investigation.

C. Holographic IS

Holographic ISs use densely packed radiation elements over spatially continuous apertures, shifting communication design toward electromagnetic-domain modeling and near-field operation. Research addresses their channel statistics, degrees of freedom, capacity, transmission schemes, and hardware realization.

  • C. Holographic IS: Holographic ISs are spatially continuous apertures with densely packed radiation elements that shape surface-propagating reference waves into desired beams.Their dense apertures motivate electromagnetic-domain rather than purely digital-domain analysis.
  • Channel modeling: Holographic-IS channel models must capture strong spatial correlation and mutual coupling caused by compact radiation-element distributions.A spatial-correlation model uses h ∼ CN(0, R), while a later model incorporates spatial and temporal correlation through a four-dimensional sinc function.
  • DoF: The degrees of freedom of line-of-sight holographic-IS channels are determined by geometric factors normalized to wavelength.A study derived an approximate closed-form expression for the performance limits of a point-to-point system.
  • System capacity: Normalized holographic-IS capacity converges to a constant as terminal density increases and wavelength approaches zero under line-of-sight channels.This result describes an asymptotic capacity limit rather than unbounded growth with element density.
  • Transmission schemes: Near-field transmission and amplitude-controlled beamforming require designs beyond conventional far-field phase-only MIMO schemes.Near-field models account for element-dependent phases and distances, while amplitude control imposes real-domain amplitude constraints on complex optimization.

3) Hardware Implementation:

Holographic IS hardware requires tunable radiation elements that control surface current distributions for dynamic beamforming. Candidate mechanisms include PIN diodes, liquid crystals, and photosensitive devices, each presenting different speed, linearity, interference, or integration trade-offs.

  • Hardware Implementation: Tunable radiation elements construct holographic patterns by controlling the surface current distribution, enabling dynamic beamforming.The section surveys electrical and optical tuning mechanisms for realizing this tunability.
  • PIN diodes: PIN-diode cELC resonators control radiation power by changing mutual inductance through bias-voltage-dependent diode states.The cELC structure combines an annular-slot metal patch with a closed loop.
  • Liquid crystal: Liquid crystals offer linear high-frequency control, flexible structural integration, and low power usage, but their slow response limits rapid-tuning applications.Their predominantly capacitive operation requires minimal currents.
  • Photosensitive devices: Photosensitive semiconductors provide rapid optical tuning and protection against electromagnetic interference, with optical-fiber integration as an additional option.Their responses are controlled by illuminating the corresponding radiation elements.
  • Potential Applications: Holographic ISs are being considered for LEO satellite communications, wireless SLAM, and ISAC applications.In ISAC, holographic patterns can alleviate beam squint in wideband transmission through their linear additivity.
  • Conclusions: The survey synthesizes reflection-based IS design issues and emerging architectures while identifying trends and open challenges toward 6G and beyond.It covers optimization, deployment, modulation, sensing, ISAC, and advanced surface architectures.
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