- Department of Electrical and Computer Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Astana, Kazakhstan
For future wireless networks beyond 5G (B5G), integrating and dynamically reconfiguring advanced technologies is crucial for achieving high spectral efficiency and ensuring massive user connectivity. This work proposes a practical and improved millimeter-wave non-orthogonal multiple access (NOMA) framework that synergistically integrates a reconfigurable intelligent surface (RIS) with fluid antenna system (FAS) receivers. The port selection diversity of FAS is utilized to enhance signal reception and aid interference suppression during successive interference cancellation (SIC). A central contribution is the development of a max–min fairness-based power allocation (PA) algorithm designed to equalize the ergodic capacities of NOMA users by maximizing the minimum achievable signal-to-interference-plus-noise ratio (SINR) under imperfect SIC conditions, ensuring a fair and balanced rate distribution. Crucially, three major practical impairment sources, such as the combined impact of channel state information (CSI) with bounded estimation error, finite-resolution RIS phase-shift quantization, and residual interference due to imperfect SIC with configurable error levels are explicitly modeled and analyzed. Simulation results evaluate the system performance across various transmit power and FAS port numbers, conclusively demonstrating that the RIS-FAS integration yields substantial gains in ergodic capacity, successfully balances spectral efficiency with user fairness, and highlights the critical trade-offs necessary for realistic networks.
1 Introduction
As the number of connected devices in future communication systems increases exponentially, the demand for fast and reliable wireless services becomes critical. It is projected that the number of connected IoT devices will almost double from 20.1 billion devices in 2025 to 39.6 billion in 2033 (Statista Research Department, 2023). The rapid growth of connected devices has raised interest in exploring advanced communication systems that enhance spectral utilization and adapt to complex propagation environments. Wireless technologies such as reconfigurable intelligent surfaces (RISs) (Shaikh et al., 2022; Rostami Ghadi et al., 2024), non-orthogonal multiple access (NOMA) (Tlebaldiyeva et al., 2021), and fluid antenna systems (FASs) have each independently demonstrated significant potential to improve system performance through intelligent channel shaping, spectrum efficiency, and spatial diversity (Tlebaldiyeva et al., 2024; Tlebaldiyeva et al., 2023). Integrating these technologies offers new degrees of freedom to improve fundamental performance metrics, especially ergodic capacity, which quantifies the long-term average achievable rate under fading channels.
RIS has gathered interest for its ability to passively shape the wireless environment via programmable phase shifts that improve base station (BS)-to-user channel propagation (Trigui et al., 2020). It offers high spectral and energy efficiency with numerous reflective elements, making it a key beyond the 5G (B5G) enabler (Hu et al., 2018).
In addition, the recent research in (Bazzi and Chafii, 2025) presented a RIS-assisted network to enhance passive radar target localization by using the RIS to establish robust links to redirect weak, target-reflected communication signals towards the radar, effectively turning communication infrastructure into a sensing asset by jointly optimizing the sensing and communication technology. Nevertheless, providing effective support for numerous users with simultaneous access is still an open challenge. One of the multiple access techniques, NOMA, differentiates itself from other traditional methods, such as time, frequency, or code multiplexing, by allowing users to simultaneously utilize the same time-frequency resource block, thus enhancing spectrum efficiency and ensuring user fairness (Huang et al., 2018). Combining the advantages of RIS and NOMA have been investigated in a number of papers since both methods are very promising. Prior research in (Vu et al., 2024a; Shaikh et al., 2022) showed that, when used in conjunction with power domain multiplexing strategies like NOMA, RIS can greatly boost system capacity and produce high data transmission rates in fading environments. Realistic fading and hardware limitations must be taken into consideration for the practical assessment of RIS-assisted millimeter-wave (mmWave) NOMA networks. In urban and indoor mmWave environments, Nakagami-
Furthermore, most existing studies on RIS and RIS-FAS-aided NOMA assume ideal hardware and perfect channel knowledge or model all non-idealities as a single effective noise term (Li et al., 2023; Shaikh et al., 2025). In practice, there are several practical noises that jointly limit the performance of the NOMA-RIS-FAS networks (Shaikh et al., 2025; Ammisetty and Ramarakula, 2025; Vu et al., 2024b). First, the acquisition of perfect channel state information (CSI) remains impossible because mmWave frequencies require element-wise CSI estimation, which becomes infeasible due to pilot overhead and feedback constraints (Li et al., 2023; Ammisetty and Ramarakula, 2025). It was established that estimation errors translate into channel-mismatch during beamforming (Li et al., 2023), NOMA power-domain user ordering (Ammisetty and Ramarakula, 2025), and degrade both capacity and fairness. Second, imperfect successive interference cancellation (SIC) leaves a non-negligible fraction of intra-cluster interference at strong users, due to channel uncertainty, decoding errors, or hardware limitations (Pandey and Bansal, 2023; Vu et al., 2024b). Especially, this residual interference becomes more pronounced when users are closely spaced in power or experience spatial correlation (Wang T. et al., 2022; Aldababsa et al., 2022). Last, the signal-dependent distortion from hardware impairments and quantization effects restricts data transfer rates when the signal-to-noise ratio reaches high levels (Qian et al., 2020). The effective diversity order decreases because of correlated fading between the RIS elements and FAS ports, which makes these imperfections more severe for user fairness. The current research lacks models that analyze RIS-assisted NOMA systems with FAS under Nakagami-
According to Monte Carlo simulation results, the proposed RIS-FAS-NOMA configuration was found to significantly increase achievable data rates while maintaining fairness, particularly for disadvantaged users, even under practical impairments. It can be observed that the increase in the number of FAS ports and RIS elements leads to an improvement in performance, thereby emphasizing the benefits of co-optimized reconfigurable systems. The simulation results confirm that higher transmit power and more RIS/FAS components enhance ergodic capacity but expose fairness issues among NOMA users. User proximity to RIS, imperfect CSI, RIS phase-shift quantization errors, and residual interference from imperfect SIC substantially impact system performance. Fairness-based PA, combined with sufficient FAS ports and well-optimized RIS elements, can mitigate these issues to some extent, although practical imperfections remain a critical bottleneck. These findings underscore the importance of balanced design in achieving both high throughput and equitable user experiences in B5G networks.
The main contributions of this work are highlighted below:
• A practical and improved mmWave NOMA network is proposed, integrating FAS-receivers and RIS, where port selection diversity of FAS enhances signal reception and aids interference suppression during SIC.
• A max–min fairness-based PA algorithm is developed to equalize the ergodic capacities of NOMA users. The algorithm maximizes the minimum achievable signal-to-interference-plus-noise ratio (SINR) under imperfect SIC conditions, ensuring a fair and balanced rate distribution.
• Three major practical impairment sources are explicitly modeled and analyzed: CSI with bounded estimation error, finite-resolution RIS phase-shift quantization, and residual interference due to imperfect SIC with configurable error levels.
• Simulation results are presented to evaluate the proposed system performance. Ergodic capacity metrics are analyzed with respect to transmit power and the number of antenna elements, illustrating trade-offs between spectral efficiency, fairness, and RIS/FAS configurations.
The paper is structured as follows. Section II details the system model, followed by the channel model and fairness-based power allocation in Sections III and IV. Finally, numerical results and conclusions are presented in Sections V and VI.
We use the following notation in the paper:
2 System model
We study an RIS-assisted NOMA network with two users as shown in Figure 1. It is assumed that a base station
We assume ideal channel state information for the
3 Channel and signal model
3.1 BS-to-RIS channel
The channel between the BS and the
where
3.2 RIS-to-user channels
The
where
3.3 Imperfect channel state information model
The imperfect channel from RIS element
where
3.4 Effective received signals with imperfect CSI and phase noise at port for both users
The received signal at the port
where
Similarly, the received signal at user 2 of the port
where
3.5 Phase error distribution due to quantization
RIS cannot generate all desired phases and, in practice, can create a limited number of phases towards the users, which is denoted by
where
3.6 Signal-to-interference-plus-noise ratio (SINR)
For the far user,
where
Near user
where
4 Fairness-based power allocation
In this section, we propose a max–min fairness-driven PA strategy to equalize the ergodic capacities of the two NOMA users in the presence of practical impairments, i.e., imperfect CSI, finite-resolution RIS phase shifts, and residual interference due to imperfect SIC. Since the ergodic capacity is a monotonically increasing function of the SINR, maximizing the minimum ergodic capacity across users is equivalent to maximizing the minimum SINR. To achieve max-min fairness, we set
Solving the quadratic equation
•
•
•
The optimal power allocation is
5 Computational complexity analysis
The computational complexity of the proposed Fairness-based NOMA-FAS algorithm is primarily determined by the system parameters, such as the RIS elements and FAS ports. For a given transmit power
6 Ergodic capacity
The performance metric of primary interest is the ergodic capacity of each user, defined as
where the expectation is taken over the random channel realizations, estimation errors
Because of the max-operation over
where
The normalized ergodic sum capacity is computed as
to fairly compare different transmit power levels and impairment scenarios.
7 Numerical results
In this section, we will investigate how the practical system noises affect the normalized ergodic capacity of the proposed system model. We discuss findings via Monte Carlo simulations run for
Figure 2 depicts the normalized ergodic capacity as a function of the number of RIS ports for different
Figure 3 illustrates the impact of the number of RIS elements on the system’s fairness, quantified using Jain’s fairness index, for different
Figure 4 illustrates the complex interplay between transmit power, number of FAS ports, and SIC error on the system’s performance. A primary observation is the significant capacity degradation caused by the non-ideal SIC, where increasing the SIC error,
Figure 5 illustrates the relationship between the normalized ergodic capacity and the number of FAS ports in a system for different numbers of RIS elements
Figure 6 illustrates the critical influence of the CSI correlation coefficient
Similarly, Figure 7 demonstrates the joint impact of
Next, Figure 8 illustrates the influence of the number of quantization bits, which is observed to impact the ergodic capacity, particularly at high transmit power. The ideal case of infinite quantization
Figure 9 investigates the combined effects of fading environment and imperfect SIC on ergodic capacity versus the number of FAS ports. The three distinct fading scenarios are clearly separated: the upper curves, corresponding to the favorable LOS channel with
8 Conclusion
This paper rigorously investigated fairness-based algorithms for NOMA networks empowered by RIS-FAS technologies under practical system noises such as imperfect CSI, hardware quantization phase errors at the RIS, and residual interference SIC. The simulation results demonstrated that poor CSI quality and severe fading at NLOS links constitute the fundamental limits on achievable capacity, often setting a hard capacity ceiling regardless of increasing transmit power or receiver diversity. A reduction in the CSI correlation coefficient from 1.0 to 0.7 resulted in a catastrophic capacity degradation of approximately
Crucially, the study demonstrates the efficacy of FAS diversity as a powerful mitigation strategy against these imperfections. Increasing the number of FAS ports proved highly beneficial in counteracting non-linear noise sources. For instance,
Building upon the findings of this study, future research will extend the proposed RIS-NOMA-FAS framework to multi-cluster scenarios, where each cluster comprises two users. While the current work demonstrates that a NOMA network with two users optimizes the balance between spectral efficiency and SIC complexity, practical large-scale deployments will require sophisticated user clustering algorithms to manage a higher density of active devices.
Data availability statement
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.
Author contributions
LT: Writing – original draft, Writing – review and editing. GN: Conceptualization, Supervision, Writing – review and editing. AD: Software, Writing – original draft. SA: Conceptualization, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – review and editing.
Funding
The author(s) declared that financial support was received for this work and/or its publication. This research is partially funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. AP22788920).
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
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Keywords: ergodic capacity, fairness optimization, FAS, NOMA, RIS, practical impairments
Citation: Tlebaldiyeva L, Nauryzbayev G, Dairanbek A and Arzykulov S (2026) Fairness optimization in RIS-FAS NOMA networks under practical impairments. Front. Commun. Netw. 7:1756675. doi: 10.3389/frcmn.2026.1756675
Received: 29 November 2025; Accepted: 12 January 2026;
Published: 17 February 2026.
Edited by:
Kin Fai (Kenneth) Tong, Hong Kong Metropolitan University, Hong Kong SAR, ChinaReviewed by:
Luciano Miuccio, University of Catania, ItalyAhmad Bazzi, New York University Abu Dhabi, United Arab Emirates
Copyright © 2026 Tlebaldiyeva, Nauryzbayev, Dairanbek and Arzykulov. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Leila Tlebaldiyeva, bHRsZWJhbGRpeWV2YUBudS5lZHUua3o=
Aigerim Dairanbek