Source-linked AI summary
Hybrid Reconfigurable Intelligent Metasurfaces: Enabling Simultaneous Tunable Reflections and Sensing for 6G Wireless Communications
George C. Alexandropoulos, Nir Shlezinger, Idban Alamzadeh, Mohammadreza F. Imani, Haiyang Zhang, Yonina C. Eldar
TL;DR
Solely reflective RISs cannot locally sense their environment and face difficult individual-channel estimation, limiting autonomous configuration and network management. This paper reviews HRISs, develops a hybrid reflecting-and-sensing design and model, and evaluates sensing-based AoA and channel estimation. The reported simulations show accurate AoA estimation with 20% sensed signal power and characterize power-splitting trade-offs in channel estimation.
Problem
Solely reflective RISs lack local sensing and make individual channel estimation difficult, complicating autonomous configuration and wireless network management.
Method
The paper reviews HRIS configurations, presents a waveguide-coupled hybrid meta-atom design and simplified simultaneous reflection-sensing model, and evaluates AoA and channel estimation.
Results
20% sensed signal power still permits accurate AoA estimation, while simulations characterize the power-splitting trade-off between estimating UTs-HRIS and HRIS-BS channels.
Takeaways & Limitations
HRIS sensing supports local AoA identification, self-configuration, and channel-estimation assistance while retaining controllable reflective operation.
Abstract
from arXiv · showhide
The latest discussions on the upcoming sixth Generation (6G) of wireless communications are envisioning future networks as a unified communications, sensing, and computing platform. The recently conceived concept of the smart radio environment, enabled by Reconfigurable Intelligent Surfaces (RISs), contributes towards this vision offering programmable propagation of information-bearing signals. Typical RIS implementations include metasurfaces with almost passive unit elements capable of reflecting their incident waves in controllable ways. However, this solely reflective operation induces significant challenges for the RIS optimization from the wireless network orchestrator. For example, RISs lack information to locally tune their reflection pattern, which can only be acquired by other network entities, and then shared with the RIS controller. Furthermore, channel estimation, which is essential for coherent RIS-empowered communications, is challenging with the available RIS designs. This article reviews the emerging concept of Hybrid reflecting and sensing RISs (HRISs), which enables metasurfaces to reflect the impinging signal in a controllable manner, while simultaneously sensing a portion of it. The sensing capability of HRISs facilitates various network management functionalities, including channel parameter estimation and localization, while giving rise to potentially computationally autonomous and self-configuring metasurfaces. We discuss a hardware design for HRISs and detail a full-wave electromagnetic proof of concept. The distinctive properties of HRISs, in comparison to their solely reflective counterparts, are highlighted and a simulation study evaluating their capability for performing full and parametric channel estimation is presented. Future research challenges and opportunities arising from the HRIS concept are also included.
I. INTRODUCTION
Conventional RISs offer programmable EM propagation but cannot sense their environment, complicating local reflection control, network management, and individual channel estimation. HRISs address these challenges by simultaneously reflecting and sensing incident signals.
- RISs use almost passive meta-atoms with programmable EM responses to shape wireless propagation for 6G communications.
- Purely reflective RISs cannot sense impinging signals, so external network entities must configure their reflection patterns through dedicated control links.
- RIS-assisted links contain separate UT-RIS and RIS-BS channels, making their individual estimation challenging with solely reflective designs.
- HRISs combine controllable reflection with sensing, enabling local signal information for network management and potentially autonomous reflection-pattern configuration.
- The article reviews HRIS configurations, presents a hardware implementation with full-wave EM simulations, and evaluates local AoA estimation and channel-estimation capabilities.
II. HRIS DESIGN AND PROOF OF CONCEPT
The proposed HRIS hardware couples reflective meta-atoms to sampling waveguides, allowing each element or group to reflect part of an incident signal while sensing another part. Varactor-controlled phase shifting provides tunable reflection patterns, and full-wave simulations demonstrate simultaneous reflection and sensing.
- Configurations of Hybrid Meta-Atoms: Two hybrid meta-atom configurations are described: simultaneous partial reflection and sensing, or switching between absorption-based sensing and reflection.
- Configurations of Hybrid Meta-Atoms: The selected HRIS configuration adds waveguides coupled to individual or grouped meta-atoms, with reception RF chains enabling local digital processing of sampled signals.
- Design Considerations: Adjacent meta-atoms require spacing below half a wavelength to detect incident phase fronts accurately, motivating a multilayer hardware structure.
- Design Considerations: Closer spacing improves beam directionality and wavefront detection but increases meta-atom count, cost, and potentially power consumption; limiting RF chains offers a balance.
- Implementation: The hybrid implementation repurposes element coupling to a waveguide for sensing, while the varactor changes effective capacitance and reflection phase.
- Full-Wave EM Simulations: At 19 GHz, a varactor-tuned hybrid meta-atom reflects and senses different signal portions while applying controllable phase shifts to steer reflected waves.
III. HRISS FOR SMART WIRELESS ENVIRONMENTS
HRISs can support conventional reflective-RIS applications while also operating with local sensing. Their sensing capability supports AoA recovery, self-configuration, and channel-estimation procedures for wireless systems.
- HRISs can extend coverage and boost connectivity by modifying the propagation profile of information-bearing EM waves.
- HRISs can use locally estimated AoAs to operate independently of a dedicated external control link.
- The section presents a model for simultaneous tunable reflection and sensing, followed by numerical evaluations of AoA recovery and full channel estimation.
A. HRIS-Empowered Wireless Communications
HRISs extend reflective RIS operation with local sensing, supporting autonomous configuration, channel estimation, and other sensing functions while retaining controllable signal reflection. These benefits introduce additional processing hardware, energy consumption, cost, and possible control-link requirements.
- A. HRIS-Empowered Wireless Communications: HRISs split impinging signals between tunable reflection and local sensing, enabling the metasurface to process received signal portions through RF chains and a digital processor.The structure uses N hybrid meta-atoms and Nr reception RF chains connected to N sampling waveguides, with N ≫ Nr.
- A. HRIS-Empowered Wireless Communications: Local AoA estimates can let an HRIS choose its phase configuration, reducing dependence on external configuration and control.The HRIS can still maintain a dedicated control link with the BS when needed.
- A. HRIS-Empowered Wireless Communications: HRISs retain reflective coverage-extension and connectivity-boosting roles while adding sensing-enabled independent operation.The HRIS can modify the propagation profile of information-bearing electromagnetic waves and use collected AoA estimates locally.
- A. HRIS-Empowered Wireless Communications: Sensing captured from UT transmissions can improve channel estimation for coherent communications and support localization, RF sensing, and RF mapping.HRISs can also convey sensed information to the BS through a control link.
- A. HRIS-Empowered Wireless Communications: Using the entire surface for sensing during acquisition phases can support channel estimation, while the HRIS fully reflects during data transmission.Blind estimation techniques can enable simultaneous channel estimation and data communication.
- A. HRIS-Empowered Wireless Communications: HRIS benefits require extra energy and cost for local signal processing, RF chains, and analog combining circuitry.The specific increase depends strongly on the implementation, while HRISs do not use an active wireless transmission mechanism for amplification.
B. Model for Simultaneous Reflection and Sensing
The HRIS model represents controllable reflection and sensing through per-meta-atom coupling and phase parameters. It encompasses purely reflective, partially receiving, and semi-passive RIS configurations while allowing adaptive hybrid operation.
- B. Model for Simultaneous Reflection and Sensing: The sensing model relates the impinging waveform to signals collected by the sensing circuitry, with implementation-dependent responses and RF-chain processing.A simplified representation uses the non-reflected portion, 1 − ρn, multiplied by a phase component.
- B. Model for Simultaneous Reflection and Sensing: The HRIS configures both reflected-energy portions and phase shifts on reflected and received paths.This operation model is illustrated in Fig. 3.
- B. Model for Simultaneous Reflection and Sensing: By setting coupling coefficients appropriately, an HRIS can realize purely passive, partially receiving, or semi-passive RIS operation.Hybrid operation adds flexibility because meta-atom settings can adapt to current conditions, facilitating self-automation and adaptivity.
- B. Model for Simultaneous Reflection and Sensing: Fig. 4 compares elevation-AoA estimation for N ∈ {144, 400} meta-atoms, uniform ρ ∈ {0.2, 0.8}, and T = 64 sensed samples against Cramér–Rao lower bounds.The figure varies both the number of meta-atoms and the coupling coefficient while reporting estimation performance.
C. Channel Estimation with HRISs
HRIS sensing supports local estimation of individual channels, while power splitting creates a trade-off between estimating the UTs-HRIS and HRIS-BS channels. Simulations also evaluate AoA and cascaded-channel estimation under different HRIS configurations.
- Full Channel Estimation: HRISs can estimate the composite UTs-HRIS channel locally and contribute to estimating the HRIS-BS channel, unlike solely reflective RISs that observe only BS-side outputs.The HRIS forwards its local estimate to the BS over an out-of-band control link.
- AoA Estimation: 20% sensed signal power still enables accurate AoA estimation, while sensing more strongly improves performance and smaller HRISs provide better accuracy.The evaluation uses N ∈ {122, 202}, coupling ρ ∈ {0.2, 0.8}, and T = 64 samples at 19 GHz.
- Full Channel Estimation: Power splitting produces a trade-off: reflecting up to 50% improves HRIS-BS channel estimation with minor effect on UTs-HRIS estimation, whereas further reflection degrades the latter with little additional benefit.The setup includes a 16-antenna BS, 8 users, 64 HRIS elements, 8 RF chains, and 30 dB reflected-signal SNR.
- Cascaded Channel Estimation: HRIS sensing improves cascaded-channel estimation compared with solely reflective RIS estimation, especially when the coupling parameters are optimized according to the available RF chains.The comparison considers fixed parameters reflecting, on average, 50% of the incoming signal and optimized parameters obtained through first-order MSE optimization.
IV. RESEARCH CHALLENGES AND OPPORTUNITIES
HRIS research must address operation protocols, physical modeling, hardware scaling, and sensing-wave coupling to establish practical gains over reflective RISs. These challenges span autonomous control, faithful electromagnetic characterization, implementation cost, and experimental validation.
- Fundamental Limits: Fundamental-limit analyses should quantify achievable-rate gains from HRIS sensing-aided communications relative to solely reflective RISs.The comparison should remain invariant to the operation of network end entities.
- Operation Protocols: HRIS sensing and computing motivate new operation protocols for integrated sensing and communications, including local direction estimation, localization, and RF mapping.These capabilities can support self-configuration, while multi-HRIS and base-station coordination may require low-latency, rate-limited control links.
- HRIS Modeling: Current performance evaluations rely on a simplified HRIS dual-operation model rather than fully physics-driven electromagnetic characterization.Practical responses may include coupled amplitude and phase parameters, as well as coupling between different meta-atoms.
- HRIS Modeling: HRIS studies should characterize the implementation-dependent power consumption and cost associated with sensing-enabled gains.This analysis is needed to understand the practical price of HRIS advantages compared with reflective RISs.
- Hardware Designs: Realizing wireless HRISs requires experimental hardware efforts from low to THz frequencies and design choices covering meta-atom arrangement, tuning, size, and phase control.Relevant phase-configuration issues include beam-steering span, grating lobes, and sidelobes.
- Hardware Designs: Waveguide coupling can multiplex signals across sampling waveguides, allowing a pre-characterized sensing matrix to support channel estimation.Directly connecting each hybrid meta-atom to a sampling waveguide can instead minimize coupling between meta-atoms.
V. CONCLUSION
The paper reviews HRISs as metasurfaces that simultaneously control reflection and sense incident signals. It presents hardware and electromagnetic evidence of feasibility, evaluates localization and channel-estimation capabilities, and identifies challenges for future 6G systems.
- V. CONCLUSION: HRISs simultaneously reflect part of an impinging signal controllably while sensing another part, unlike solely reflective RISs.This hybrid operation is the paper’s defining distinction from conventional reflective designs.
- V. CONCLUSION: The paper presents an HRIS design and full-wave electromagnetic proof of concept demonstrating hardware feasibility.It also develops a simplified model for HRIS reconfigurability.
- V. CONCLUSION: The evaluation examines local angle-of-arrival identification and channel estimation in comparison with solely reflective RISs.The discussion covers both the operating capabilities and the research challenges associated with HRISs.