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Metasurface-Based RIS

Updated 20 October 2025
  • Metasurface-based RIS are engineered electromagnetic structures with electrically controlled meta-atoms that program phase, amplitude, and reflection properties.
  • They integrate active and passive components like varactors and PIN diodes to enable dynamic beamforming and improve wireless propagation for 5G/6G networks.
  • Key challenges include real-time adaptation, managing mutual coupling, and leveraging advanced DSP and machine learning for optimal network performance.

Metasurface-based reconfigurable intelligent surfaces (RIS) are engineered electromagnetic structures comprised of electrically controlled subwavelength scattering elements (meta-atoms), designed to impose programmable reflection, phase, and amplitude profiles on incident waves to modify and optimize wireless propagation environments. Distinct from traditional passive surfaces, metasurface-based RIS integrate active electronic components—such as varactors, PIN diodes, or amplifying circuits—into their unit cells, enabling real-time adaptation of the surface's electromagnetic properties at fine spatial and spectral granularity. This framework underpins recent advances in wireless communications, especially for 5G/6G networks, where smart environments, beamforming, energy efficiency, security, and flexible waveform manipulation are pivotal.

1. Fundamental Principles and Architectural Variants

Reconfigurable intelligent surfaces (RIS), sometimes called intelligent reflecting surfaces (IRS) or large intelligent metasurfaces (LIMs), are planar assemblies of programmable meta-atoms, each capable of imparting electronically tunable phase and, in advanced cases, amplitude shifts on incident electromagnetic (EM) waves. At the physical layer, each unit cell typically consists of a metallic patch (or resonator) on a dielectric substrate, integrated with a tunable element (such as a PIN diode, varactor, or MEMS switch), granting coarse (binary, n-bit) or continuous control over its reflection impedance.

Metasurface-based RIS are deployed in wireless scenarios as passive (controlling only phase/amplitude), active (incorporating amplifying or power-collecting devices), hybrid (active/passive integration), or digital (bit-coded) surfaces:

  • Binary/Discrete-Phase RIS: Unit cells toggle between two (binary) or n states (e.g., 0°, 90°, 180°, 270°), facilitating quantized beamforming or codebook-based modulation (Gros et al., 2021, Zhao et al., 28 Jul 2024).
  • Continuous-Phase RIS: Continuous tuning (e.g., via varactors) yields smooth phase control, enhancing beam directivity and power efficiency (Ataloglou et al., 8 Apr 2025).
  • Active and Hybrid RIS: Some cells incorporate negative-resistance circuits or amplifiers for in-band signal amplification and out-of-band filtering, with hybrid schemes balancing amplification and power constraints (Feng et al., 2023, Wu et al., 31 Dec 2024).
  • Digital RIS (DRIS): Surfaces whose meta-atoms are digitally programmed, enabling the direct application of digital signal processing (DSP) at the physical layer and facilitating advanced coding techniques (Ndjiongue et al., 2021).
  • Arbitrary Waveform Generated RIS (AWG-RIS): Architectures that decouple amplitude (waveform) and phase (beamforming), allowing direct modulation of arbitrary baseband signals without altering the spatial pattern (Dong et al., 5 Jul 2024).

2. Electromagnetic Modeling and Metasurface Engineering

The EM response of metasurface-based RIS is rigorously modeled either via full-wave simulation or analytical frameworks:

  • Each unit cell's reflection coefficient is described as Γ(t)=Y0−Ys(t)Y0+Ys(t)\Gamma(t) = \frac{Y_0 - Y_s(t)}{Y_0 + Y_s(t)}, with Y0Y_0 being the free-space admittance and Ys(t)Y_s(t) the surface admittance programmable via the internal electronic state (Hodge et al., 2023).
  • For broadband/frequency-agnostic design, meta-atom behavior is strongly influenced by resonance characteristics, substrate parameters, and geometry; meta-learning frameworks such as MetaFAP predict unit-cell-level scattering properties across broad bands and cell designs with sub-millisecond speed and order-of-magnitude improvement in MSE/MAE (Murshed et al., 19 Mar 2025).

Advanced analytical models range from equivalent circuit models (ECM), supporting rapid parametric sweeps under arbitrary incidence and polarization for fast RIS optimization (Nousiou et al., 9 Apr 2025), to volume–surface integral equations and method-of-moments (MoM) solvers that capture both macro-scale beamforming and evanescent surface-wave phenomena necessary for amplitude tapering and complex sector beam synthesis (Ataloglou et al., 8 Apr 2025). Accurate modeling is critical for beamforming, particularly where mutual coupling and stacking (e.g., beyond-diagonal RIS for holographic MIMO systems) become significant (Nerini et al., 19 Feb 2024).

3. Beamforming, Beamsteering, and Wavefront Control

RIS beamforming exploits the spatial programmability of large metasurface arrays, in which optimal or jointly optimized phase shifts steer reflected wavefronts to desired angular directions or focal points. Salient techniques include:

  • 3D Beamforming: Full-dimensional array control at the base station (BS) or RIS enables joint tuning of azimuth (Ï•\phi) and elevation (θ\theta) angles, maximizing SNR by exploiting both direct and RIS-reflected paths (Razavizadeh et al., 2020).
  • Surface-Wave Assisted Beamforming: Subwavelength unit cells, when closely spaced, support auxiliary evanescent waves for in-plane amplitude control—crucial for sector patterns or variable beamwidths. Sectorized beams with controlled mainlobe width (30°–60°) and high steering accuracy are achieved using integral-equation-optimized metasurfaces (Ataloglou et al., 8 Apr 2025).
  • Multi-Focus and Vortex Beams: By rapidly switching (sub-millisecond) among precomputed phase states, fully programmable 2-bit RIS arrays can generate spot beams (with independently controlled focus points) or helical vortex beams (OAM modes), supporting advanced modalities such as dynamic beam tracking and Doppler-domain signal modulation (Zhao et al., 28 Jul 2024).
  • Beamforming in Relay/Amplification Contexts: Amplifying and filtering RIS (AF-RIS) architectures combine power combining networks with 2-bit phase control, achieving both high in-band gain (over 20 dB) and precise steering, while suppressing interference through sharp out-of-band filtering (Wu et al., 31 Dec 2024).

4. Advanced Modulation and Integrated Communication

Metasurface-based RIS platforms underpin advanced modulation schemes and integration with other communication modalities:

  • Arbitrary Waveform Modulation: AWG-RIS architectures allow independent analog amplitude modulation (waveform) and phase directives (beam), supporting arbitrary baseband signal embedding (MIMO backscatter, secure transmission, ISAC) while retaining fixed beam patterns (Dong et al., 5 Jul 2024).
  • Index Modulation (IM): RIS enable spatial, frequency, and temporal index modulation (e.g., spatial shift keying, subcarrier IM, space–time shift keying) by controlling which meta-atoms, subcarriers, or time slots participate in modulation (Hodge et al., 2023). This is achieved by adjusting the programmable bias (e.g., varactor diodes) or switching among digital codebooks. Performance advantages are evident in SNR, BER, and capacity metrics versus classical schemes.
  • Space-Time Coding and Concurrent Modulation/Beam Steering: Binary-coded space–time metasurfaces support simultaneous data modulation and beam directionality. Periodic binary codes applied to each cell result in harmonics whose phases are mapped to specific steering angles. Experimental setups demonstrate BPSK/QPSK/8-PSK/16-PSK metasurface-based modulation in realistic environments (Gholami et al., 27 Oct 2024).

5. System-Level Applications, Optimization, and Network Planning

Metasurface-based RIS directly impact large-scale network performance via:

  • Capacity and Coverage Enhancement: RIS arrays with optimized phase profiles yield significant SNR and capacity gains in both LOS and NLOS scenarios. Proper geometric configuration, increase in RIS element count, and optimized beamforming angles maximize network performance, with system-level simulations confirming multi-dB power and SINR benefits (Gu et al., 2022, Razavizadeh et al., 2020).
  • Energy Harvesting and Physical Layer Security: Metasurface-coated devices, by concentrating EM energy, enable ultra-low-power (ULP) operation and significant improvements in secrecy performance through spatial power control at the receiver, with up to 30 dB gain ratios between users and eavesdroppers (Tsiftsis et al., 2020).
  • Real-Time Adaptation and Frequency-Agnostic Optimization: Meta-learning frameworks allow rapid, frequency-independent tuning of RIS designs, supporting dynamic spectrum access, carrier aggregation, and scalable deployment (Murshed et al., 19 Mar 2025).
  • Network Planning with AI: The optimal deployment and configuration of RIS in large-scale environments (e.g., railway stations) is facilitated with deep reinforcement learning agents (e.g., D-RISA), leveraging digital twins and ray tracing to incrementally optimize placement, association, and phase profiles, achieving up to 10 dB SNR improvement and reduced computational time (Encinas-Lago et al., 2023, Albanese et al., 2022).

6. Practical and Experimental Implementations

Recent prototypes demonstrate both the feasibility and versatility of metasurface-based RIS platforms:

  • High-Frequency Prototypes: Binary-phase metasurfaces at mmWave (28.5 GHz) and C-band demonstrate rapid (up to 100 kHz) phase state switching, energy efficiency, and robust performance for both near-field reflectarray and far-field access-point extension scenarios (Gros et al., 2021, Ataloglou et al., 8 Apr 2025).
  • 2-bit/Hybrid Arrays: Full-array, 2-bit phase-quantized architectures with less than 0.6 dB insertion loss and rapid reconfiguration enable dynamic beamforming, multi-spot and vortex beams, and time-domain modulation (Doppler shifts), all validated through laboratory measurement (Zhao et al., 28 Jul 2024).
  • Active and Filtering RIS: Devices integrating amplifier/filter circuits into the metasurface structure yield concurrent gain and interference suppression, with compact hardware footprints (one-tenth area per required power vs. passive RIS) (Wu et al., 31 Dec 2024).
  • Arbitrary Waveform Generation: Demonstrated AWG-RIS prototypes show passive, directionally-stable synthesis of complex waveforms, with multiple analog input channels and FPGA-based beamforming controllers (Dong et al., 5 Jul 2024).

7. Challenges, Trade-offs, and Future Directions

Design and deployment of metasurface-based RIS face intrinsic trade-offs and open problems:

  • Control Complexity vs. Hardware Scalability: Full independent element control increases channel state and wiring overhead; wave-controlled architectures or basis-function programming provide a low-dimensional alternative, improving hardware efficiency while aligning with EM constraints (Ayanoglu et al., 2022).
  • Passive vs. Active Functionality: While passive designs ensure low power and cost, amplifying-hybrid architectures confer improved range, efficiency, and anti-interference but require advanced power management and circuit integration (Feng et al., 2023, Wu et al., 31 Dec 2024).
  • Mutual Coupling and Beyond-Diagonal Control: Accurate EM modeling must include near-field mutual coupling, especially for dense/stacked arrangements. "Beyond-diagonal" RIS matrices enable single-layer optimal performance, reducing complexity relative to multi-layer diagonal designs (Nerini et al., 19 Feb 2024).
  • DSP and Algorithmic Integration: The intersection of digital metamaterials, real-time DSP, and meta-learning algorithms enables frequency-agnostic, environment-adaptive, and multi-functional RIS, paving the way toward programmable wireless environments (Ndjiongue et al., 2021, Murshed et al., 19 Mar 2025).
  • Security and Sensing: Decoupled amplitude/phase RIS and spatial power shaping architectures open new avenues for secure communications and integrated sensing/communication (ISAC) scenarios, where intentional modulation of EM signatures is beneficial (Dong et al., 5 Jul 2024).

Ongoing research is focused on extending metasurface-based RIS to multi-RIS scenarios, 3D holographic beamforming, ultra-broadband operation, physics-informed learning for rapid control, and joint optimization of surface and waveform parameters in dynamically evolving wireless environments.

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