Design and Operation Principles of a Wave-Controlled Reconfigurable Intelligent Surface

TL;DR

This paper tackles the wiring and control complexity of large RIS by introducing a wave-controlled RIS that uses N standing-wave modes to bias M elements per row, significantly reducing wiring while enabling beamforming and null-steering. It develops a realistic varactor-based reflection model including mutual coupling, and compares two AC-to-DC bias conversion methods—envelope detector and sample-and-hold—alongside several optimization algorithms (Weight Ranking, Least Squares, Weighted LS, and Simulated Annealing) to maximize SNR or SLNR. Through extensive simulations, the authors show that the wave-controlled approach can achieve near-ideal beamforming gains and deep nulls with considerably less hardware complexity, making practical mmWave/RIS implementations more feasible. The work provides a comprehensive framework for modeling, control signal distribution, and optimization that supports scalable RIS deployment with significant reductions in wiring and signaling overhead while preserving high performance.

Abstract

A Reflective Intelligent Surface (RIS) consists of many small reflective elements whose reflection properties can be adjusted to change the wireless propagation environment. Envisioned implementations require that each RIS element be connected to a controller, and as the number of RIS elements on a surface may be on the order of hundreds or more, the number of required electrical connectors creates a difficult wiring problem, especially at high frequencies where the physical space between the elements is limited. A potential solution to this problem was previously proposed by the authors in which "biasing transmission lines" carrying standing waves are sampled at each RIS location to produce the desired bias voltage for each RIS element. This solution has the potential to substantially reduce the complexity of the RIS control. This paper presents models for the RIS elements that account for mutual coupling and realistic varactor characteristics, as well as circuit models for sampling the transmission line to generate the RIS control signals. For the latter case, the paper investigates two techniques for conversion of the transmission line standing wave voltage to the varactor bias voltage, namely an envelope detector and a sample-and-hold circuit. The paper also develops a modal decomposition approach for generating standing waves that are able to generate beams and nulls in the resulting RIS radiation pattern that maximize either the Signal-to-Noise Ratio (SNR) or the Signal-to-Leakage-plus-Noise Ratio (SLNR). Extensive simulation results are provided for the two techniques, together with a discussion of computational complexity.

Figures (25)

• Figure 1: Wave-controlled RIS made of two physical layers. Top layer: $M$ RIS elements in each row along $x$; each element is connected to a varactor diode. Bottom layer: $N$ standing waves along the biasing transmission lines (TLs) to create the biasing voltages when sampled at each RIS element. Each row is controlled only by the connection at the left where $N$ frequencies are injected by a waveform generator.
• Figure 2: RIS formed by a periodic arrangement of square metallic conductors on a grounded dielectric substrate. The polarization of the incident electric field is along $x$. Varactor diodes are between patches, used as tunable capacitors when reversed biased.
• Figure 3: Circuit model of the varactor. (a) SPICE model provided by the vendor. (b) Simplified equivalent RLC series ($R_v (V)$, $L_{sp}$, $C_v (V)$) circuit model. The values of $C_v$ and $R_v$ vary with the applied bias voltage.
• Figure 4: Equivalent capacitance and resistance of the varactor model in Fig. \ref{['fig:Varactor_model']} (b) as a function of the varactor biasing voltage. Knowledge of these two functions of $V$ leads to the analytic expression of the reflection coefficient $\phi_m(V)$ via (\ref{['eq:ReflCoeff']}), accounting for losses and RIS electromagnetic couplings.
• Figure 5: Equivalent analytical circuit model of the RIS. $Z_{RIS}$ is seen from the left.