⚡ electrical engineering

Fluid Antennas Meet Intelligent Surfaces: Security Analysis of NOMA Systems Under Hardware Impairments

This paper presents a comprehensive analytical framework evaluating the security performance of NOMA systems integrating fluid antennas and reconfigurable intelligent surfaces under realistic hardware impairments, revealing that while the synergy offers significant security gains, practical hardware limitations ultimately impose fundamental performance ceilings that dictate critical design trade-offs.

Original authors: Tuo Wu, Jianchao Zheng, Xiazhi Lai, Maged Elkashlan, Hyundong Shin, Naofal Al-Dhahir

Published 2026-03-10

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CC BY 4.0

Original authors: Tuo Wu, Jianchao Zheng, Xiazhi Lai, Maged Elkashlan, Hyundong Shin, Naofal Al-Dhahir

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 send a secret letter to a friend in a crowded, noisy city, but a sneaky spy is trying to intercept it. This paper is about building the ultimate "secret mail system" using two futuristic technologies, while admitting that our real-world tools aren't perfect.

Here is the breakdown using simple analogies:

1. The Players: The "Liquid" Antenna and the "Smart" Mirror

To send your secret, you have two superpowers:

Fluid Antennas (The Liquid Antenna): Imagine a traditional antenna is like a fixed radio tower. A Fluid Antenna is like a liquid metal blob that can instantly change its shape or move its "listening ear" to any of 50 different spots on a small stick. It can instantly find the clearest spot to hear your friend, dodging the noise and interference.
Reconfigurable Intelligent Surfaces (The Smart Mirror): Imagine a wall covered in thousands of tiny, programmable mirrors. If a building blocks your signal, you can tell these mirrors to bend the radio waves around the corner, creating a "virtual path" to your friend.

The Goal: Combine these two. Use the liquid antenna to find the best spot and the smart mirrors to bounce the signal perfectly, making it impossible for the spy to catch the message.

2. The Problem: The "Imperfect Tools"

In the real world, our electronics aren't perfect. They have "hardware impairments."

The Analogy: Imagine trying to whisper a secret through a cracked, foggy window (the hardware) while using a slightly bent mirror (the smart surface). Even if you have the best liquid antenna in the world, the crack in the window distorts the sound.
The Reality: Real radios have "phase noise" (shaky timing), "amplitude errors" (wrong volume), and "quantization" (digital rounding errors). These act like static noise that gets louder as you try to shout (increase power).

3. The Big Discovery: The "Ceiling Effect"

The authors wanted to know: If we just keep adding more liquid antenna spots or bigger smart mirrors, will we eventually become 100% secure?

The Answer is No.

The Metaphor: Imagine you are trying to fill a bucket with water (security) using a hose (signal power). But the bucket has a hole in the bottom (hardware imperfections).
- If you turn the hose up higher (more power), the bucket fills up faster at first.
- But eventually, the water leaking out of the hole equals the water coming in. No matter how hard you turn the hose, the water level stops rising. It hits a "ceiling."
The Finding: The paper proves that hardware flaws create a "performance ceiling." You can't just buy more antennas to fix bad hardware. If your electronics are cheap or old, your security will hit a limit, no matter how smart your system is.

4. The Solution: Finding the "Sweet Spot"

Since we can't fix the hardware perfectly, the paper offers a guide on how to design the system to get the most out of what we have:

Don't Overbuy: Adding more "liquid antenna" spots helps at first, but after about 6 or 8 spots, the extra benefit is tiny. It's like having 100 ears when you only need 6 to hear clearly.
Quality Over Quantity: It is better to buy high-quality, expensive hardware (a clean window) than to buy a million cheap, broken mirrors. Fixing the "hole in the bucket" is more important than turning up the hose.
The "NOMA" Trick: The system uses a technique called NOMA (Non-Orthogonal Multiple Access). Think of this as sending two letters in one envelope: one for your friend (low power) and one for the public (high power). The friend knows how to peel off the public letter to read the secret one, but the spy gets confused by the layers. The paper shows how to balance the power so the friend gets it clearly, but the spy gets confused, even with the "cracked window."

5. The Takeaway for Everyday Life

This research tells engineers and companies:

Futuristic tech is great: Combining liquid antennas and smart mirrors is a game-changer for security.
But don't ignore the basics: If you build a super-secure system with cheap, noisy electronics, it will fail. The "hardware quality" is the most critical factor.
Balance is key: You don't need the most expensive system possible. You just need the right amount of antennas and good enough hardware to stay below that "security ceiling."

In short: You can have the most advanced spy-proof technology in the world, but if your microphone is broken, the spy will still hear you. This paper helps us figure out exactly how good the microphone needs to be to keep our secrets safe.

1. Problem Statement

The paper addresses a critical gap in the emerging field of secure wireless communications: the lack of comprehensive analysis regarding the synergy between Fluid Antenna Systems (FAS) and Reconfigurable Intelligent Surfaces (RIS) in Non-Orthogonal Multiple Access (NOMA) systems when subjected to Hardware Impairments (HIs).

Context: While FAS offers dynamic spatial adaptability and RIS provides intelligent signal reflection, their combination in NOMA systems is theoretically promising for Physical Layer Security (PLS).
The Challenge: Practical deployment is hindered by HIs (e.g., phase noise, amplifier non-linearities, quantization errors). These impairments introduce signal-dependent distortion noise that degrades Signal-to-Interference-plus-Noise Ratio (SINR).
The Core Question: Can the spatial diversity gains from FAS and the beamforming gains from RIS effectively compensate for the performance ceilings imposed by hardware imperfections in short-packet secure communications?
Specific Focus: The paper analyzes the Average Secure Block Error Rate (BLER) for a downlink NOMA system where a Base Station (BS) communicates with a Central User (CU) and an Eavesdropper (EU) via two separate RISs, assuming direct links are blocked.

2. Methodology

The authors develop a rigorous analytical framework to model and evaluate the system under realistic constraints.

System Model:
- Architecture: A BS with a single antenna transmits superimposed signals to a CU and an EU. Both users are equipped with FAS (selecting the best port out of $L$ ports) and are assisted by dedicated RISs ( $M$ elements each).
- Channel Model: Rayleigh flat fading is assumed for BS-RIS and RIS-user links (non-line-of-sight). Spatial correlation of FAS ports is modeled using a 3D Clarke's isotropic scattering model (sinc-function correlation).
- Hardware Impairments (HIs): Modeled as additive Gaussian distortion noise scaling with the received signal power ( $\varrho^2$ ). This affects both the legitimate user and the eavesdropper.
- Decoding: The CU performs Successive Interference Cancellation (SIC). The EU is modeled as a "worst-case" eavesdropper capable of ideal SIC to decode the confidential message.
Analytical Techniques:
- Piecewise Linear Approximation: To handle the intractable Gaussian Q-functions in the BLER expressions, the authors approximate the BLER functions ( $\Psi, \Phi, \Xi$ ) using piecewise linear segments.
- Block-Correlation Approximation (BCA): To manage the complexity of the correlated FAS port selection, the Toeplitz correlation matrix is approximated by a block-diagonal structure.
- Central Limit Theorem (CLT): For large numbers of RIS elements ( $M$ ), the cascaded channel gain is approximated as a Gaussian random variable.
- Gauss-Chebyshev Quadrature: Used to compute the double integrals required for the expected values of the BLER components, significantly reducing computational complexity compared to Monte Carlo simulations.
- Critical Point Analysis: The integration domain is partitioned into distinct cases (6 for $E[\Psi\Phi]$ and 6 for $E[\Psi\Xi]$ ) based on the relative ordering of critical SINR thresholds derived from the piecewise approximations.

3. Key Contributions

Novel Closed-Form Expressions: The paper derives tractable closed-form expressions for the Average Secure BLER of the central user. These expressions account for the complex interplay between FAS spatial correlation, RIS reflection, NOMA power allocation, and HIs.
First Comprehensive HI Analysis: This is the first study to quantify how RF front-end imperfections specifically degrade the security performance of FAS-RIS NOMA systems. It reveals that HIs create fundamental performance limits.
Theoretical Insights on Performance Ceilings: The analysis proves that HIs introduce a performance ceiling. Even with infinite transmit power or increased spatial diversity (more FAS ports), the Secure BLER cannot drop below a certain floor determined by the hardware impairment level ( $\varrho^2$ ).
Practical Design Guidelines: The paper provides actionable guidelines for system designers, including:
- Hardware Quality vs. Diversity: Investing in higher-quality RF components (lower $\varrho^2$ ) yields more significant security gains than simply adding more FAS ports or RIS elements once a certain threshold is reached.
- Optimal Configurations: Identification of optimal power allocation strategies and FAS port counts (diminishing returns observed beyond 6–8 ports).

4. Key Results

Validation: Extensive simulations confirm that the proposed analytical framework matches simulation results with high accuracy, validating the piecewise linear and BCA approximations.
Impact of HIs:
- HIs cause a "cliff effect" in performance. When the impairment level exceeds a threshold (e.g., $\varrho^2 > 0.04$ ), the Secure BLER degrades exponentially, regardless of other system improvements.
- The system exhibits a SINR ceiling at high transmit powers ( $P \to \infty$ ), where the SINR converges to $a_C / \varrho^2_C$ , preventing the BLER from reaching zero.
FAS and RIS Benefits:
- Despite HIs, FAS-RIS systems significantly outperform conventional fixed-antenna systems (by approximately one order of magnitude in BLER).
- Increasing the number of RIS elements ( $M$ ) and FAS ports ( $L$ ) improves security, but with diminishing returns. Most gains are realized within the first 6–8 FAS ports.
Trade-offs:
- Security vs. Reliability: Stricter security constraints (lower information leakage $\delta$ ) result in higher BLER floors.
- Power Allocation: An optimal power allocation coefficient ( $a_C \approx 0.4-0.5$ ) exists. Under severe HIs, the optimal point shifts slightly, but the U-shaped performance curve remains.
Robustness: The findings hold true for both Rayleigh and Rician fading models, confirming the robustness of the design guidelines.

5. Significance

This paper is significant for the following reasons:

Realism: It moves beyond idealized theoretical models by incorporating realistic hardware constraints, which are often the bottleneck in deploying 6G technologies like FAS and RIS.
Security Benchmarking: It establishes a lower bound on achievable security performance, showing that hardware quality is a decisive factor. If hardware is too poor, the theoretical benefits of FAS-RIS synergy cannot be fully realized.
Design Efficiency: By providing analytical expressions and lookup-table strategies, the paper enables efficient offline system optimization and online parameter adaptation without the need for computationally expensive simulations.
Future Direction: It highlights that for secure NOMA systems, hardware quality is as critical as algorithmic complexity. System designers must prioritize RF component quality alongside spatial diversity strategies to achieve reliable secure communications.