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Fluid antenna systems paired with rate-splitting reduce outage probability by up to 92 percent versus fixed antennas while enabling fairness optimization in multiuser MISO links.

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Closed-form outage analysis and fairness optimization for spatially correlated FAS-enabled RSMA in multiuser MISO systems, showing up to 92% OP reduction versus fixed antennas.

T0 review reviewed 2026-06-26 challenge →

load-bearing objection The paper supplies closed-form outage expressions for RSMA over correlated fluid antennas in MISO plus a simple LP fairness solver, but the reported gains sit on top of the one-factor and quadrature approximations. the 2 major comments →

arxiv 2606.22287 v1 pith:W7RK4YGV submitted 2026-06-21 eess.SP

Outage Analysis and Fairness Design for Spatially Correlated FAS-Enabled RSMA Systems

Jinyuan Liu , Yong Liang Guan , Tuo Wu , Hong Niu , Kai-Kit Wong , Bruno Clerckx This is my paper
classification eess.SP
keywords fluid antenna systemrate-splitting multiple accessoutage probabilityfairness optimizationspatial correlationMISO downlinkzero-forcing precoding
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper develops closed-form outage probability expressions for a downlink multiuser MISO network that uses fluid antennas for dynamic port selection and rate-splitting to manage interference through common and private message parts. It employs a block correlation model, one-factor construction, and generalized Gauss-Laguerre quadrature to obtain tractable expressions under zero-forcing and maximum-ratio transmission precoding. These expressions support a fairness formulation that minimizes the worst-user outage via a low-complexity iterative algorithm with linear-program checks. Numerical validation shows the combination delivers large reliability gains over fixed-position baselines and equalizes user performance with a 1 dB SNR improvement for the weakest user. A reader would care because the results supply both analytical tools and concrete design methods for interference-limited networks that need high reliability.

Core claim

The central claim is that a spatially correlated FAS-enabled RSMA system admits closed-form outage probability expressions derived via block correlation, one-factor construction, and generalized Gauss-Laguerre quadrature, and that these expressions allow a fairness-oriented optimization minimizing the maximum outage probability whose solution equalizes user reliability and yields up to 92 percent outage reduction relative to fixed-position antennas together with a 1 dB SNR gain for the worst user at fixed outage level.

What carries the argument

Block correlation model for fluid antenna ports combined with one-factor construction and generalized Gauss-Laguerre quadrature, which produces the closed-form outage probability expressions used for both analysis and fairness optimization.

Load-bearing premise

The chosen block correlation model for fluid antenna ports, together with the one-factor construction, produces outage expressions that remain accurate under the linear precoding schemes examined.

What would settle it

Monte Carlo simulation of outage probability under the exact block correlation model and linear precoders deviates from the closed-form expressions by more than a few percent across the tested port counts and rates.

Watch this falsifier. Get emailed when new claim-graph text bears on it.

If this is right

  • FAS-RSMA achieves up to 92 percent lower outage probability than fixed-position antenna baselines across varied port counts and channel conditions.
  • The fairness-oriented design equalizes reliability across users without requiring additional power.
  • A low-complexity algorithm with linear-program feasibility check solves the min-max outage problem in closed form per iteration.
  • The analytical expressions remain valid for both zero-forcing and maximum-ratio transmission precoding.
  • Performance gains hold for different target rates and spatial correlation strengths.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • If the closed-form expressions scale well, they could support real-time port selection algorithms in hardware prototypes.
  • The fairness gain for the worst user suggests the method may help satisfy uniform quality-of-service targets in dense deployments.
  • Extending the block model to time-varying ports would test whether the outage reduction persists under mobility.
  • The 92 percent figure is tied to the specific linear precoders; nonlinear precoding might alter the observed gap to the fixed-antenna baseline.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

2 major / 1 minor

Summary. The paper studies outage analysis for spatially correlated fluid antenna system (FAS) enabled rate-splitting multiple access (RSMA) in multiuser MISO downlink with zero-forcing and maximum-ratio transmission precoding. It derives closed-form outage probability expressions using a block correlation model, one-factor construction, and generalized Gauss-Laguerre quadrature. It also develops a fairness design that minimizes the worst-user outage probability using a linear program feasibility check, with numerical results showing significant performance gains over fixed-position antenna systems.

Significance. The work provides analytical expressions and an optimization framework for FAS-RSMA systems, which could aid in designing reliable 6G networks. The use of standard techniques (one-factor construction, Gauss-Laguerre quadrature, linear programming) for derivations and the inclusion of numerical validation are strengths. If the approximations hold, the reported 92% outage reduction and 1 dB fairness gain would be impactful for interference management in dense networks.

major comments (2)
  1. [Numerical results] The 92% OP reduction and fairness gains are obtained from the closed-form expressions rather than direct simulation. The derivations rest on the block correlation model, one-factor construction, and generalized Gauss-Laguerre quadrature; the manuscript must include quantitative Monte Carlo validation in the numerical results section for the specific correlation strengths and port counts examined to confirm the approximations introduce negligible bias.
  2. [Fairness design] The fairness-oriented design claims a low-complexity algorithm with linear-program feasibility check yielding a closed-form solution per iteration. The integration of the OP expressions into the LP must be shown explicitly to ensure the solution remains tractable and does not rely on post-hoc parameter fitting.
minor comments (1)
  1. [Abstract] The abstract introduces 'one-factor construction' without a brief parenthetical explanation, which may hinder readers unfamiliar with the technique.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the detailed and constructive feedback on our manuscript. We have carefully considered each major comment and provide point-by-point responses below. Where revisions are needed, we have updated the manuscript accordingly.

read point-by-point responses

  1. Referee: [Numerical results] The 92% OP reduction and fairness gains are obtained from the closed-form expressions rather than direct simulation. The derivations rest on the block correlation model, one-factor construction, and generalized Gauss-Laguerre quadrature; the manuscript must include quantitative Monte Carlo validation in the numerical results section for the specific correlation strengths and port counts examined to confirm the approximations introduce negligible bias.

    Authors: We appreciate this observation. While the manuscript includes Monte Carlo simulations to validate the analytical expressions in Section V, we acknowledge that more quantitative comparisons (such as relative errors or bias metrics) for the specific parameters would strengthen the validation. In the revised manuscript, we will add tables or figures showing the percentage error between the closed-form OP and Monte Carlo simulations for the examined correlation strengths and port counts, confirming that the approximations introduce negligible bias. revision: yes

  2. Referee: [Fairness design] The fairness-oriented design claims a low-complexity algorithm with linear-program feasibility check yielding a closed-form solution per iteration. The integration of the OP expressions into the LP must be shown explicitly to ensure the solution remains tractable and does not rely on post-hoc parameter fitting.

    Authors: We agree that explicit demonstration is necessary. In the original submission, Section IV describes the substitution of the closed-form outage probability expressions into the linear program formulation, resulting in a feasibility check that yields a closed-form solution per iteration without parameter fitting. To address this comment, we will revise the manuscript to include the explicit equations showing the integration of the OP expressions into the LP constraints and objective, ensuring full transparency and tractability. revision: yes

Circularity Check

0 steps flagged

No significant circularity; derivations rely on standard approximations and are self-contained

full rationale

The paper's core claims rest on deriving closed-form outage probability expressions from a block correlation model via one-factor construction and generalized Gauss-Laguerre quadrature, followed by a linear-program-based fairness optimization. These steps use explicit mathematical reductions and numerical validation against simulations, without any fitted parameters renamed as predictions, self-definitional loops, or load-bearing self-citations that collapse results to inputs by construction. The 92% OP reduction and fairness gains are outputs of the derived expressions rather than tautological re-statements of modeling assumptions.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Based solely on the abstract; the paper relies on standard wireless channel assumptions (e.g., fading distributions compatible with the correlation model) and mathematical approximations whose details are not visible.

reviewed 2026-06-26 · how reviews work

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Cite this review

Pith. "Pith review of Outage Analysis and Fairness Design for Spatially Correlated FAS-Enabled RSMA Systems." pith.science (2026). https://pith.science/paper/W7RK4YGV

@misc{pith2026260622287,
  author       = {Pith},
  title        = {Pith review of: Outage Analysis and Fairness Design for Spatially Correlated FAS-Enabled RSMA Systems},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/W7RK4YGV}},
  note         = {Machine review of arXiv:2606.22287}
}
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read the original abstract

Sixth-generation (6G) systems target higher reliability, denser connectivity, and tighter interference control. {Within this context, rate-splitting multiple access (RSMA) is envisioned as a promising candidate to enhance interference management in future wireless networks by flexibly splitting messages into a common and a private part, while fluid antenna systems (FAS) offer the potential to improve spatial selectivity through dynamic port reconfiguration.} Combining RSMA and FAS therefore enables efficient interference control and adaptive antenna utilization in multiuser multi-input single-output (MISO) networks. However, deriving closed-form outage probability (OP) expressions and tractable user fairness optimization in this scenario remains scarce in the literature. This paper studies a multiuser MISO downlink that jointly leverages RSMA and FAS. We develop a spatial correlation model for FAS using block correlation and incorporate linear precoding with zero-forcing and maximum-ratio transmission. Within this model, we derive closed-form OP expressions using a one-factor construction and generalized Gauss-Laguerre quadrature. Building on these expressions, we formulate a fairness objective that minimizes the worst-user OP and propose a low-complexity algorithm with a linear-program feasibility check to obtain the closed-form solution per iteration. Numerical results across different port counts, channel conditions, and target rates validate the analytical analysis, show that FAS-RSMA reduces OP by up to 92% relative to the fixed-position antenna (FPA) baseline, and demonstrate that fairness-oriented design equalizes user reliability while delivering a 1 dB SNR gain for the worst user at a fixed outage level.

Figures

Figures reproduced from arXiv: 2606.22287 by Bruno Clerckx, Hong Niu, Jinyuan Liu, Kai-Kit Wong, Tuo Wu, Yong Liang Guan.

Figure 1
Figure 1. Figure 1: The proposed multiuser MISO downlink FAS-RSMA system framework. The precoding vectors are designed according to a hybrid ZF￾MRT principle2 , shown as wn,u = wˆ n,u ∥hn,u∥ , wc = X u∈U wn,u, (3) where hn,u = [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: OP versus SNR for three users under different FAS configurations with Rec = 1, Re1 = 2.3, Re2 = 2.0, and Re3 = 1.8. 0 1 2 3 4 5 6 SNR (dB) 10-4 10-3 10-2 10-1 100 Outage Probability User 1, L=3 User 1, L=4 User 2, L=3 User 2, L=4 User 3, L=3 User 3, L=4 User 1, Simulation User 2, Simulation User 3, Simulation (a) Fading figure parameter m = 1 0 1 2 3 4 5 6 SNR (dB) 10-6 10-5 10-4 10-3 10-2 10-1 100 Outage … view at source ↗
Figure 3
Figure 3. Figure 3: OP versus SNR for three users under various channel conditions and antenna settings with Rec = 1, Re1 = 2.3, Re2 = 2.0, and Re3 = 1.8. 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 Common rate (bps/Hz) 10-4 10-3 10-2 10-1 100 Outage Probability User 1 User 2 User 3 User 1, Simulation User 2, Simulation User 3, Simulation Invalid region [PITH_FULL_IMAGE:figures/full_fig_p010_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: OP comparison for N = 10 ports under different common-rate thresholds with private-rate targets Re1 = 2.3, Re2 = 2.0, and Re3 = 1.8. indicate that, despite the spatial correlation induced by closely spaced ports, FAS can still realize additional port-selection diversity, which in turn improves reliability compared with the FPA system. 0 1 2 3 4 5 6 SNR (dB) 10-4 10-3 10-2 10-1 100 Outage Probability FPA-RS… view at source ↗
Figure 7
Figure 7. Figure 7: demonstrates the per-user OP for three users under baseline equal power splits (dashed line) where tc = 0.3 and t1 = t2 = t3 = (1 − tc)/3, and the proposed BCOPA￾designed common and private power allocation (solid line). Without optimization, a clear disparity is observed across users. User 1 consistently exhibits the highest OP, whereas User 3 achieves the lowest, and the gap persists over the entire SNR … view at source ↗
Figure 6
Figure 6. Figure 6: contrasts the min-max OP (left y-axis) and the average CPU time (right y-axis) of the proposed BCOPA algorithm against the ES algorithm and a simplified exhaustive-search baseline with common-only optimization (ESCO), where pri￾vate streams share equal power and only the common-stream power is optimized. As observed, the min-max OP curves of BCOPA and ES overlap across the entire SNR range, indicat￾ing tha… view at source ↗
Figure 8
Figure 8. Figure 8: OP comparison among the proposed FAS-RSMA scheme and conventional FAS-ZF and FAS-MMSE precoding schemes under L = 32 and U = 16. ports. Closed-form OP expressions were derived based on a block-correlation model, hybrid ZF-MRT precoding, and generalized Gauss-Laguerre quadrature. A min-max OP design was then formulated and solved by the proposed BCOPA algo￾rithm. Numerical results validated the analysis, de… view at source ↗

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Works this paper leans on

52 extracted references · 2 canonical work pages

  1. [1]

    A tutorial on fluid antenna system for 6G networks: En- compassing communication theory, optimization methods and hardware designs,

    W. K. New et al., “A tutorial on fluid antenna system for 6G networks: En- compassing communication theory, optimization methods and hardware designs,” IEEE Commun. Surv. Tutor. , vol. 27, no. 4, pp. 2325-2377, Aug. 2025

    2025

  2. [2]

    Fluid antenna systems enabling 6G: Principles, applica- tions, and research directions

    T. Wu et al., “Fluid antenna systems enabling 6G: Principles, applications, and research directions,” IEEE Wireless Commun., early access, 2025, doi: 10.1109/MWC.2025.3629597

    work page doi:10.1109/mwc.2025.3629597 2025

  3. [3]

    Rate-splitting multiple access: Fundamentals, survey, and future research trends,

    Y . Mao, O. Dizdar, B. Clerckx, R. Schober, P . Popovski, and H. V . Poor, “Rate-splitting multiple access: Fundamentals, survey, and future research trends,” IEEE Commun. Surv. Tutor., vol. 24, no. 4, pp. 2073-2126, 2022

    2073

  4. [4]

    A new achievable rate region for the interference channel,

    T. Han and K. Kobayashi, “A new achievable rate region for the interference channel,” IEEE Trans. Inf. Theory , vol. 27, no. 1, pp. 49- 60, 1981

    1981

  5. [5]

    Rate splitting for MIMO wireless networks: A promising PHY -layer strategy for LTE evolution,

    B. Clerckx, H. Joudeh, C. Hao, M. Dai, and B. Rassouli, “Rate splitting for MIMO wireless networks: A promising PHY -layer strategy for LTE evolution,” IEEE Commun. Mag. , vol. 54, no. 5, pp. 98-105, 2016

    2016

  6. [6]

    Rate-splitting multiple access for downlink communication systems: Bridging, generalizing, and out- performing SDMA and NOMA,

    Y . Mao, B. Clerckx, and V . O. K. Li, “Rate-splitting multiple access for downlink communication systems: Bridging, generalizing, and out- performing SDMA and NOMA,” EURASIP J. Wireless Commun. Netw. , vol. 2018, no. 1, p. 133, May. 2018

    2018

  7. [7]

    Sum-rate maximization for linearly precoded downlink multiuser MISO systems with partial CSIT: A rate-splitting approach,

    H. Joudeh and B. Clerckx, “Sum-rate maximization for linearly precoded downlink multiuser MISO systems with partial CSIT: A rate-splitting approach,” IEEE Trans. on Comm. , vol. 64, no. 11, pp. 4847-4861, Nov. 2016

    2016

  8. [8]

    A rate splitting strategy for massive MIMO with imperfect CSIT,

    M. Dai, B. Clerckx, D. Gesbert, and G. Caire, “A rate splitting strategy for massive MIMO with imperfect CSIT,” IEEE Trans. Wireless Commun. , vol. 15, no. 7, pp. 4611-4624, Jul. 2016

    2016

  9. [9]

    Max-min fairness of K-user cooperative rate-splitting in MISO broadcast channel with user relaying,

    Y . Mao, B. Clerckx, J. Zhang, V . O. Li, and M. A. Arafah, “Max-min fairness of K-user cooperative rate-splitting in MISO broadcast channel with user relaying,” IEEE Trans. Wireless Commun. , vol. 19, no. 10, pp. 6362-6376, Oct. 2020

    2020

  10. [10]

    Rate-splitting unifying SDMA, OMA, NOMA, and multicasting in MISO broadcast channel: A simple two-user rate analysis,

    B. Clerckx, Y . Mao, R. Schober, and H. V . Poor, “Rate-splitting unifying SDMA, OMA, NOMA, and multicasting in MISO broadcast channel: A simple two-user rate analysis,” IEEE Wireless Commun. Lett. , vol. 9, no. 3, pp. 349-353, Nov. 2019

    2019

  11. [11]

    Rate-splitting multiple access for intelligent reflecting surface aided multi-user communications,

    A. Bansal et al., “Rate-splitting multiple access for intelligent reflecting surface aided multi-user communications,” IEEE Trans. Veh. Technol. , vol. 70, no. 9, pp. 9217-9229, Sep. 2021. 14

    2021

  12. [12]

    Rate-splitting multiple access for downlink multiuser MIMO: Precoder optimization and PHY layer design,

    A. Mishra, Y . Mao, O. Dizdar, and B. Clerckx, “Rate-splitting multiple access for downlink multiuser MIMO: Precoder optimization and PHY layer design,” IEEE Trans. Commun. , vol. 70, no. 2, pp. 874-890, Feb. 2022

    2022

  13. [13]

    A primer on rate-splitting multiple access: Tutorial, myths, and frequently asked questions,

    B. Clerckx et al. , “A primer on rate-splitting multiple access: Tutorial, myths, and frequently asked questions,” IEEE J. Sel. Areas Commun. , vol. 41, no. 5, pp. 1265-1308, 2023

    2023

  14. [14]

    Rate- splitting multiple access: Finite constellations, receiver design, and SIC- free implementation,

    S. Zhang, B. Clerckx, D. Vargas, O. Haffenden, and A. Murphy, “Rate- splitting multiple access: Finite constellations, receiver design, and SIC- free implementation,” IEEE Trans. Commun. , vol. 72, no. 9, pp. 5319- 5333, Sep. 2024

    2024

  15. [15]

    Power allocation for high mobility OTFS-RSMA system with path-selective one-tap receiver,

    J. Liu et al. , “Power allocation for high mobility OTFS-RSMA system with path-selective one-tap receiver,” IEEE Wireless Commun. Lett. , vol. 14, no. 3, pp. 661-665, Mar. 2025

    2025

  16. [16]

    Rate-splitting multiple access for 6G networks: Ten promising scenarios and applications,

    J. Park, B. Lee, J. Choi, H. Lee, N. Lee et al., “Rate-splitting multiple access for 6G networks: Ten promising scenarios and applications,” IEEE Network, vol. 38, no. 3, pp. 128-136, Oct. 2023

    2023

  17. [17]

    Outage, capacity, and error performance of downlink RSMA-based systems: Analysis and resource optimization,

    T. -H. Vu et al. ,“Outage, capacity, and error performance of downlink RSMA-based systems: Analysis and resource optimization,” IEEE Trans. Commun., vol. 73, no. 8, pp. 6868-6883, Aug. 2025

    2025

  18. [18]

    FARS: Elevating rate-splitting multiple access in non- territorial networks with intelligent fluid antenna system,

    S. Zhang et al. , “FARS: Elevating rate-splitting multiple access in non- territorial networks with intelligent fluid antenna system,” IEEE J. Sel. Areas Commun. , vol. 44, pp. 1045-1060, Sep. 2025

    2025

  19. [19]

    Performance limits of fluid antenna systems,

    K. K. Wong, A. Shojaeifard, K.-F. Tong, and Y . Zhang, “Performance limits of fluid antenna systems,” IEEE Commun. Lett. , vol. 24, no. 11, pp. 2469-2472, Nov. 2020

    2020

  20. [20]

    Fluid antenna system,

    K.-K. Wong et al. , “Fluid antenna system,” IEEE Trans. Wireless Commun., vol. 20, no. 3, pp. 1950-1962, Mar 2021

    1950

  21. [21]

    A new spatial block-correlation model for fluid antenna systems,

    P . Ram´ırez-Espinosa, D. Morales-Jimenez, and K. K. Wong, “A new spatial block-correlation model for fluid antenna systems,” IEEE Trans. Wireless Commun. , vol. 23, no. 11, pp. 15829-15843, Nov. 2024

    2024

  22. [22]

    Pro- grammable meta-fluid antenna for spatial multiplexing in fast fluctuating radio channels,

    B. Liu, K.-F. Tong, K. K. Wong, C.-B. Chae, and H. Wong, “Pro- grammable meta-fluid antenna for spatial multiplexing in fast fluctuating radio channels,” Opt. Express , vol. 33, no. 13, pp. 28898-28915, 2025

    2025

  23. [23]

    Design and implementation of mmWave surface wave enabled fluid antennas and experimental results for fluid antenna multiple access,

    Y . Shen et al. , “Design and implementation of mmWave surface wave enabled fluid antennas and experimental results for fluid antenna multiple access,” arXiv preprint , arXiv:2405.09663, May 2024

    work page arXiv 2024

  24. [24]

    A novel pixel-based reconfigurable antenna applied in fluid antenna systems with high switching speed,

    J. Zhang et al. , “A novel pixel-based reconfigurable antenna applied in fluid antenna systems with high switching speed,” IEEE Open J. Antennas Propag., vol. 6, no. 1, pp. 212-228, Feb. 2025

    2025

  25. [25]

    Fluid antenna multiple access,

    K.-K. Wong and K.-F. Tong, “Fluid antenna multiple access,” IEEE Trans. Wireless Commun. , vol. 21, no. 7, pp. 4801-4815, Jul. 2022

    2022

  26. [26]

    Copula-based performance analysis for fluid antenna systems under arbitrary fading channels,

    F. R. Ghadi et al., “Copula-based performance analysis for fluid antenna systems under arbitrary fading channels,” IEEE Commun. Lett. , vol. 27, no. 11, pp. 3068-3072, Nov. 2023

    2023

  27. [27]

    An efficient sum-rate maximization algorithm for fluid antenna-assisted ISAC system,

    Q. Zhang et al., “An efficient sum-rate maximization algorithm for fluid antenna-assisted ISAC system,” IEEE Commun. Lett. , vol. 29, no. 1, pp. 200-204, Jan. 2025

    2025

  28. [28]

    A survey on artificial noise for physical layer security: Opportunities, technologies, guidelines, advances, and trends,

    H. Niu et al. , “A survey on artificial noise for physical layer security: Opportunities, technologies, guidelines, advances, and trends, ” IEEE Commun. Surv. Tutor. , vol. 28, pp. 341-381, Sep. 2026

    2026

  29. [29]

    Fluid antenna system: New insights on outage probability and diversity gain,

    W. K. New, K. K. Wong, H. Xu, K. F. Tong and C.-B. Chae, “Fluid antenna system: New insights on outage probability and diversity gain,” IEEE Trans. Wireless Commun. , vol. 23, no. 1, pp. 128-140, Jan. 2024

    2024

  30. [30]

    Scalable FAS: A new paradigm for array signal process- ing,

    T. Wu et al. , “Scalable FAS: A new paradigm for array signal process- ing,” IEEE J. Sel. Topics Signal Process. , early access, 2026

    2026

  31. [31]

    Channel estimation for FAS-assisted multiuser mmWave systems,

    H. Xu et al. , “Channel estimation for FAS-assisted multiuser mmWave systems,” IEEE Commun. Lett. , vol. 28, no. 3, pp. 632-636, Mar. 2024

    2024

  32. [32]

    Channel estimation and reconstruction in fluid an- tenna system: Oversampling is essential,

    W. K. New et al. , “Channel estimation and reconstruction in fluid an- tenna system: Oversampling is essential,” IEEE Trans. Wireless Commun., vol. 24, no. 1, pp. 309-322, Jan. 2025

    2025

  33. [33]

    Topological perspective of large-scale multi-cell deployment of excitable waveguide dielectrics,

    Y . Zhu, Z. Ding, and X. Y ou, “Topological perspective of large-scale multi-cell deployment of excitable waveguide dielectrics,” IEEE Wireless Commun. Lett. , vol. 15, pp. 151–155, 2026

    2026

  34. [34]

    Cell-free fluid antenna multiple access networks,

    T. Han, Y . Zhu, K.-K. Wong, G. Zheng, and H. Shin, “Cell-free fluid antenna multiple access networks,” IEEE Trans. Wireless Commun. , vol. 24, no. 9, pp. 7237–7251, Sep. 2025

    2025

  35. [35]

    Fluid Antenna Enabled Compact Ultra Massive Antenna Array for Satellite Communications,

    T. Han, Y . Zhu, G. Zheng and P . -D. Arapoglou, “Fluid Antenna Enabled Compact Ultra Massive Antenna Array for Satellite Communications,” IEEE J. Sel. Areas Commun. , vol. 44, pp. 1077-1091, 2026

    2026

  36. [36]

    Exploring fairness for FAS-assisted communication systems: from NOMA to OMA,

    J. Y ao et al. , “Exploring fairness for FAS-assisted communication systems: from NOMA to OMA,” IEEE Trans. Wireless Commun. , vol. 24, no. 4, pp. 3433-3449, April 2025

    2025

  37. [37]

    Fluid antenna system liberating multiuser MIMO for ISAC via deep reinforcement learning,

    C. Wang et al. , “Fluid antenna system liberating multiuser MIMO for ISAC via deep reinforcement learning,” IEEE Trans. Wireless Commun. , vol. 23, no. 9, pp. 10879-10894, Sep. 2024

    2024

  38. [38]

    Fluid antenna-assisted ISAC systems,

    L. Zhou et al. , “Fluid antenna-assisted ISAC systems,” IEEE Wireless Commun. Lett. , vol. 13, no. 12, pp. 3533- 3537, Dec. 2024

    2024

  39. [39]

    FAS-RIS communication: Model, analysis, and optimiza- tion,

    J. Y ao et al. , “FAS-RIS communication: Model, analysis, and optimiza- tion,” IEEE Trans. Veh. Technol. , vol. 74, no. 6, pp. 9938-9943, Jun. 2025

    2025

  40. [40]

    Revisiting spatial block-correlation model for fluid antenna systems: from constant to variable correlations,

    X. Lai et al., “Revisiting spatial block-correlation model for fluid antenna systems: from constant to variable correlations,” IEEE J. Sel. Areas Commun., vol. 44, pp. 1335-1351, Oct. 2025

    2025

  41. [41]

    Variable block-correlation modeling and optimization for secrecy analysis in fluid antenna systems,

    T. Wu et al. , “Variable block-correlation modeling and optimization for secrecy analysis in fluid antenna systems,” IEEE Trans. Wireless Commun., vol. 25, pp. 15069-15085, Apr. 2026

    2026

  42. [42]

    Movable antennas for wireless communication: Opportu- nities and challenges,

    L. Zhu et al., “Movable antennas for wireless communication: Opportu- nities and challenges,” IEEE Commun. Mag. , vol. 62, no. 6, pp. 114–120, Jun. 2024

    2024

  43. [43]

    Modeling and performance analysis for movable antenna enabled wireless communications,

    L. Zhu, W. Ma, and R. Zhang, “Modeling and performance analysis for movable antenna enabled wireless communications,” IEEE Trans. Wireless Commun. , vol. 23, no. 6, pp. 6234–6250, Jun. 2024

    2024

  44. [44]

    MIMO capacity characterization for movable antenna systems,

    W. Ma, L. Zhu, and R. Zhang, “MIMO capacity characterization for movable antenna systems,” IEEE Trans. Wireless Commun. , vol. 23, no. 4, pp. 3392–3407, Apr. 2024

    2024

  45. [45]

    Movable antenna enabled near-field communications: Channel modeling and performance optimization,

    L. Zhu et al. , “Movable antenna enabled near-field communications: Channel modeling and performance optimization,” IEEE Trans. Com- mun., vol. 73, no. 9, pp. 7240–7256, Sep. 2025

    2025

  46. [46]

    Fluid antenna-aided robust secure transmission for RSMA-ISAC systems,

    C. Zhang et al. “Fluid antenna-aided robust secure transmission for RSMA-ISAC systems,” arXiv preprint , 2025

    2025

  47. [47]

    Fluid antenna-aided rate-splitting multiple access,

    F. R. Ghadi et al. “Fluid antenna-aided rate-splitting multiple access,” IEEE Trans. Veh. Technol. , vol. 75, no. 2, pp. 3417–3422, Aug. 2025

    2025

  48. [48]

    Phase-mismatched STAR-RIS with FAS-assisted RSMA users,

    F. R. Ghadi et al. “Phase-mismatched STAR-RIS with FAS-assisted RSMA users,” IEEE Trans. Commun., vol. 74, pp. 2032–2046, Dec. 2025

    2032

  49. [49]

    UA V-relay assisted RSMA fluid antenna system: Outage probability analysis,

    F. R. Ghadi et al. “UA V-relay assisted RSMA fluid antenna system: Outage probability analysis,” IEEE Wireless Commun. Lett. , vol. 14, no. 9, pp. 2907–2911, Sep. 2025

    2025

  50. [50]

    FAS-RSMA: Can fluid antennas elevate RSMA perfor- mance?,

    J. Liu et al. , “FAS-RSMA: Can fluid antennas elevate RSMA perfor- mance?,” IEEE Trans. Commun. , vol. 74, pp. 6476-6492, Mar. 2026

    2026

  51. [51]

    Fluid Antennas Meet Rate-Splitting Multiple Access: A New Path Forward for 6G Networks,

    J. Liu et al. , “Fluid Antennas Meet Rate-Splitting Multiple Access: A New Path Forward for 6G Networks,” arXiv preprint , Apr. 2026

    2026

  52. [52]

    I. S. Gradshteyn and I. M. Ryzhik, Table of Integrals, Series, and Products, 7th ed. San Diego, CA: Academic, 2007

    2007

This paper was first reviewed by grok-4.3 on June 26, 2026.