⚡ electrical engineering

Liquid Crystal-Based RIS Loss-Trade-Off Analysis

This paper investigates the fundamental trade-off between insertion loss and phase-shift range in liquid crystal-based reconfigurable intelligent surfaces (LC-RIS) at mmWave bands, demonstrating how this relationship impacts the optimization of transmit power and achievable data rates for multi-user systems.

Original authors: Bowu Wang, Mohamadreza Delbari, Robin Neuder, Alejandro Jiménez-Sáez, Vahid Jamali

Published 2026-07-27

📖 6 min read🧠 Deep dive

CC BY 4.0

Original authors: Bowu Wang, Mohamadreza Delbari, Robin Neuder, Alejandro Jiménez-Sáez, Vahid Jamali

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine you are trying to shout a secret message across a crowded, noisy stadium. If you just stand there and yell, your voice might get lost. But what if you had a giant, magical wall of mirrors that could catch your voice, bounce it perfectly, and aim it straight at your friend? That is the dream behind a technology called a Reconfigurable Intelligent Surface, or RIS. Think of it as a smart, programmable mirror for radio waves. Instead of just reflecting light like a bathroom mirror, an RIS can tweak the waves as they bounce off, bending them to reach people who are hidden behind buildings or far away.

To make these mirrors work, especially at the super-fast speeds of modern 5G and future 6G networks (which use millimeter waves), scientists are looking at a special material called Liquid Crystal (LC). You might know liquid crystals from your smartphone screen; they are the stuff that lets pixels change color. In this new tech, they act like tiny, tunable knobs that can twist radio waves. The big idea is that these LC mirrors could be cheap, use very little battery power, and be made huge to cover entire cities. But, like any engineering project, there's a catch. You can't just get everything for free. If you make the "knobs" too small to save space and energy, they might not be able to twist the waves as much as you need. If they can't twist enough, the signal gets messy. If you make them too big to twist perfectly, they might get "stiff" and lose some of the signal's strength as it passes through. This paper is all about finding the perfect size for these knobs so the whole system works best.

The Balancing Act of the Magic Mirror

This paper dives into a specific puzzle regarding those liquid crystal "knobs" on the RIS. The researchers, working at the Technical University of Darmstadt, wanted to figure out the "Goldilocks" zone: not too big, not too small, but just right. They focused on a trade-off that hadn't been fully explored yet: the tug-of-war between how much the mirror can twist a signal (the phase-shift range) and how much signal gets lost in the process (insertion loss).

Imagine you have a garden hose. If you make the hose shorter, the water flows through with less resistance (less loss), but you lose the ability to aim the stream in a wide arc. If you make the hose longer, you gain the ability to aim the water in a full circle, but the water loses pressure as it travels through the extra length. In the world of these LC mirrors, the "length" is the physical size of the liquid crystal cell. The paper explains that if you make the cell shorter, the signal passes through with less loss (like less friction in the hose), but the mirror loses its ability to twist the wave through a full circle (360 degrees). If you make it longer, it can twist the wave perfectly, but the signal gets weaker as it travels through the material.

The Simulation Game

To solve this, the authors didn't just guess; they built a computer simulation. They set up a virtual world with a base station (the shouters), a giant RIS mirror made of 100 tiny liquid crystal cells (a 10x10 grid), and four different users (the listeners) standing in various spots around the mirror. Some users were standing right in the "mirror reflection" spot, where the signal bounces naturally, while others were standing off to the side, needing the mirror to do some heavy lifting to aim the signal their way.

The goal of their simulation was simple: make sure every user got a clear signal (a specific quality of service) while using the least amount of power possible from the base station. They ran the numbers over and over, changing the length of the liquid crystal cells to see what happened.

What They Found

The results showed a clear pattern, which they visualized in their graphs. For the user standing right in the "mirror reflection" spot, the best setup was actually to use the shortest possible liquid crystal cells. Why? Because that user didn't need the mirror to twist the signal much at all; they just needed it to bounce. Using a long, complex cell would only introduce unnecessary signal loss. In this case, the "loss" of twisting ability didn't matter because no twisting was needed.

However, for the users standing off to the side, the story was different. These users needed the mirror to twist the signal significantly to aim the beam at them. If the researchers used short cells (low loss), the mirror couldn't twist the signal enough, and the base station had to shout much louder (use more power) to compensate. But if they used longer cells, the mirror could twist perfectly, but the signal was so weak from the "friction" of the material that the base station still had to shout louder.

The simulation suggested that there is a "sweet spot" for the length of the liquid crystal cells. It isn't always the shortest, and it isn't always the longest. It depends entirely on where the users are standing. If the users are scattered in a wide area, the mirror needs a bit more "twisting power" (a longer cell), even if it means accepting a tiny bit more signal loss. If the users are all in one specific spot, a shorter, more efficient cell is better.

The Takeaway

In short, this paper suggests that there is no single "perfect" design for these smart mirrors. The best design depends on the situation. The authors found that by carefully adjusting the length of the liquid crystal components, engineers can balance the loss of signal strength against the ability to steer the signal. This balance allows the system to use less power overall, making future wireless networks more energy-efficient. While these findings are based on computer simulations and not yet tested in a real-world stadium, they provide a crucial roadmap for how to build these next-generation mirrors so they don't waste energy while trying to keep our phones connected.

Technical Summary: Liquid Crystal-Based RIS Loss-Trade-Off Analysis

Problem Statement
Reconfigurable Intelligent Surfaces (RISs) utilizing Liquid Crystal (LC) technology offer a promising solution for millimeter-wave (mmWave) communications due to their low power consumption, scalability, and continuously tunable phase shifts. However, LC-based phase shifters employing a delay-line architecture face an intrinsic physical trade-off: the maximum achievable phase-shift range is directly coupled with the insertion loss. Specifically, shorter phase shifter lengths reduce insertion loss but constrain the maximum phase shift, potentially falling below the ideal $2\pi$ range and degrading system performance. While the energy efficiency of RIS-assisted systems has been studied generally, and the impact of phase-dependent insertion loss has been modeled in other contexts, this specific trade-off between phase-shift range and insertion loss in LC-RIS-assisted wireless systems had not been previously investigated.

Methodology
The authors formulate a power minimization problem where a Base Station (BS) and an LC-RIS are configured to minimize transmit power while satisfying a specific Quality of Service (QoS) requirement (minimum Signal-to-Noise Ratio, SNR) for multiple users. The system model considers a narrow-band downlink with a BS equipped with a Uniform Planar Array (UPA) and an RIS composed of $N$ LC unit cells serving $K$ single-antenna Mobile Users (MUs) via Time-Division Multiple Access (TDMA).

Key modeling aspects include:

Channel Model: Given the large size of the RIS and elevated installation, Near-Field (NF) Line-of-Sight (LOS) channels are modeled using Rician fading with high K-factors. Direct BS-MU links are assumed blocked.
Loss Model: The relationship between the physical length of the LC phase shifter ( $l$ ), the maximum phase shift ( $\Delta\omega_{max}$ ), and the insertion loss ( $|\Omega|^2_{dB}$ ) is derived based on the Figure of Merit (FoM). The analysis establishes that decreasing $l$ reduces loss but also reduces $\Delta\omega_{max}$ .
Optimization Framework: The problem is non-convex due to the coupling of beamforming vectors, phase shifts, and the phase-shift range constraints. The authors propose an iterative algorithm using Alternating Optimization (AO) to decompose the problem into two subproblems:
1. Beamformer Design: Optimizing the transmit beamforming vector ( $q_k$ ) using Maximum Ratio Transmission (MRT) for fixed phase shifts.
2. RIS Configuration: Optimizing the phase-shift vector and the maximum phase-shift range ( $\omega_{max}$ ) to maximize the effective channel gain. This subproblem is addressed by reformulating the non-convex constraints using penalty methods and convex relaxation techniques (specifically handling the rank-one constraint and non-convex phase constraints).

The algorithm iterates through different values of $\omega_{max}$ to find the optimal configuration that minimizes total transmit power for a given FoM and user location distribution.

Key Contributions

Identification of a Fundamental Trade-off: The paper explicitly characterizes the trade-off between the total transmit power and the achievable data rate as a function of the LC phase-shift range. It demonstrates that there is no universally optimal phase shifter length; rather, an optimal length exists that is dependent on the specific scenario (user locations and coverage requirements).
Joint Optimization Algorithm: The authors develop a computational framework that dynamically adjusts RIS phase shifts and accounts for both the restricted phase-shift range and the associated insertion loss, moving beyond the assumption of ideal, lossless RIS elements.
Scenario-Dependent Insights: The study provides a method to determine the optimal LC phase shifter length for specific deployment scenarios, balancing the reduction of insertion loss against the need for sufficient phase control to steer signals effectively.

Simulation Results
Simulation results, conducted with a 28 GHz carrier frequency and a 10x10 RIS element array, reveal several critical findings:

Impact of User Location: For users located in the specular reflection direction (mirror-like behavior), a minimal phase-shift range is sufficient. In these cases, increasing the phase-shift range (by lengthening the LC cell) only introduces additional insertion loss without improving performance, thereby increasing the required transmit power.
Non-Specular Users: For users deviating from the specular direction, a broader phase-shift range is necessary. Here, the trade-off manifests clearly: a larger $\omega_{max}$ allows for better signal focusing but incurs higher insertion loss. The simulations show that as the coverage area (radius of user distribution) increases, both the required transmit power and the optimal $\omega_{max}$ increase.
FoM Influence: The Figure of Merit (FoM) significantly influences the optimal design. A higher FoM (lower loss per degree of phase shift) allows for a broader feasible phase-shift range, which is particularly beneficial for users requiring complex phase compensation.

Significance and Claims
The paper claims to be the first to investigate this specific loss-performance trade-off in LC-RIS-assisted wireless communications. The authors assert that their work provides a fundamental insight for system designers: there exists a scenario-dependent optimal LC phase shifter length that achieves the best trade-off between total transmission power and data rate. By identifying this optimal point, the proposed approach enables more energy-efficient wireless communications using LC-RIS, avoiding the pitfalls of blindly maximizing phase-shift range (which increases loss) or blindly minimizing length (which restricts beamforming capability). The study emphasizes that while the analysis was conducted in a simplified scenario to isolate the trade-off, the findings are relevant for designing practical, energy-efficient RIS systems.

Technical Summary: Liquid Crystal-Based RIS Loss-Trade-Off Analysis

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