pith. sign in

arxiv: 2605.22040 · v1 · pith:7THULAFNnew · submitted 2026-05-21 · 💻 cs.IT · math.IT

Finite-Aperture Planar Fluid Antenna Array

Zhentian Zhang , Jingyuan Xu , Kai-Kit Wong , Hao Jiang , Zaichen Zhang , Hyundong Shin This is my paper

Pith reviewed 2026-05-22 04:23 UTC · model grok-4.3

classification 💻 cs.IT math.IT
keywords fluid antenna systemsplanar arraysCramér-Rao boundport placementgeometric inertia matrixangle estimationprecision-ambiguity trade-offfinite aperture
0
0 comments X

The pith

A 2x2 geometric inertia matrix sets the Cramér-Rao bound for joint angle estimation in finite planar fluid antenna arrays.

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

The paper builds an analytical framework for planar fluid antenna arrays under finite aperture limits. It shows that random port placement yields a minimum inter-port distance following a Rayleigh distribution whose mean shrinks only as one over the number of ports, unlike the faster decay seen in one-dimensional cases. A universal Cramér-Rao bound for simultaneous elevation and azimuth estimation is then expressed through the determinant and eigenstructure of a 2 by 2 geometric inertia matrix built from the port coordinates. Both the trace and determinant of this matrix stay unchanged when the azimuth look direction rotates. Maximizing the determinant to tighten the bound pushes candidate ports outward to the aperture edges, which simultaneously raises the chance of spatial ambiguity created by higher sidelobes.

Core claim

The central claim is that a 2x2 geometric inertia matrix, whose entries are second-moment sums over the chosen port locations, fully determines the Cramér-Rao bound on joint elevation-azimuth estimation error; its determinant and eigenvalues therefore quantify the effect of any port configuration, its trace and determinant remain constant under azimuth rotation, and any attempt to enlarge the determinant necessarily increases sidelobe-induced ambiguity.

What carries the argument

The 2x2 geometric inertia matrix whose entries are formed from the squared coordinates and cross-products of the selected port positions inside the rectangular aperture; it directly supplies the Fisher information matrix for the angle parameters.

If this is right

  • Minimum inter-port distance under uniform random placement obeys a Rayleigh distribution whose mean scales as O(M^{-1}).
  • Trace and determinant of the geometric inertia matrix are invariant to the azimuth look direction.
  • Maximizing the determinant of the inertia matrix to reduce the CRB forces ports toward the aperture boundary.
  • Boundary concentration raises the level of sidelobe-induced spatial ambiguity in the angle estimates.

Where Pith is reading between the lines

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

  • Layouts that deliberately cluster ports near the four corners could achieve the same determinant gain without relying on random sampling.
  • The invariance to azimuth suggests that a single fixed layout may suffice for wide-azimuth scanning scenarios.
  • Dynamic port selection algorithms could periodically re-optimize the inertia determinant while monitoring sidelobe levels in real time.

Load-bearing premise

The derivation of the minimum-distance distribution and the inertia matrix treats the candidate ports as placed uniformly at random across the rectangular aperture.

What would settle it

A Monte Carlo experiment that draws many uniform random port sets and checks whether the empirical distribution of minimum pairwise distances deviates from the predicted Rayleigh law would refute the first result; likewise, a measured angle-estimation variance that fails to track the inertia-matrix formula would refute the bound.

Figures

Figures reproduced from arXiv: 2605.22040 by Hao Jiang, Hyundong Shin, Jingyuan Xu, Kai-Kit Wong, Zaichen Zhang, Zhentian Zhang.

Figure 1
Figure 1. Figure 1: Empirical and theoretical PDF of the minimum inter-p [PITH_FULL_IMAGE:figures/full_fig_p009_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: CRB vs. SNR and geometric determinant for multiple [PITH_FULL_IMAGE:figures/full_fig_p009_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Trade-off curves vs. β0 for the default configuration: (top) CRB and det(Lgeo); (bottom) number of interior ports. F. Computational Complexity Phase I runs in O(Nc). Phase II iterates (M − 4) rounds, each scanning at most Nc candidates with O(M) operations per candidate, yielding a total of O((M − 4) · Nc · M). Remark 8 (Regularized Term β): The diversity weight β provides control over the precision-divers… view at source ↗
Figure 4
Figure 4. Figure 4: Port placement (top row) and beam pattern in the [PITH_FULL_IMAGE:figures/full_fig_p011_4.png] view at source ↗
read the original abstract

Fluid antenna systems (FASs) are emerging as a reconfigurable-aperture technology that expands physical-layer design beyond fixed, rigid antenna geometries. While the \emph{fading diversity} of FASs -- which exploits spatial channel fluctuations for signal enhancement and interference avoidance -- has been widely studied, the \emph{geometry diversity} created by reconfigurable port placement remains far less understood, particularly for planar architectures under finite-aperture constraints. This paper develops a systematic analytical framework for finite-aperture planar fluid antenna arrays (FAAs). First, we derive a closed-form characterization of the minimum inter-port distance under uniform random placement over a rectangular aperture and show that it follows a Rayleigh law. Its mean scales as $\mathcal{O}(M^{-1})$, in sharp contrast to the $\mathcal{O}(M^{-2})$ behavior in the linear case in which $M$ represents the number of candidate ports, revealing a fundamentally more favorable packing geometry in two dimensions. Secondly, we establish a universal Cram\'{e}r-Rao bound (CRB) for joint elevation-azimuth estimation, governed by a $2\times 2$ \emph{geometric inertia matrix} whose determinant and eigenstructure fully capture the role of port placement in estimation precision. We further prove that both the trace and determinant of this matrix are invariant to the azimuth look direction. Third, we uncover an intrinsic \emph{precision--ambiguity trade-off}: maximizing the geometric determinant to minimize the CRB drives ports toward the aperture boundary, but simultaneously increases sidelobe-induced spatial ambiguity.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

0 major / 3 minor

Summary. This paper develops a systematic analytical framework for finite-aperture planar fluid antenna arrays. It derives a closed-form characterization of the minimum inter-port distance under uniform random placement over a rectangular aperture, showing that it follows a Rayleigh law with mean scaling as O(M^{-1}). It establishes a universal Cramér-Rao bound for joint elevation-azimuth estimation governed by a 2×2 geometric inertia matrix, proving that both the trace and determinant of this matrix are invariant to the azimuth look direction. It further identifies an intrinsic precision-ambiguity trade-off in which maximizing the determinant of the inertia matrix drives ports toward the aperture boundary while increasing sidelobe-induced spatial ambiguity.

Significance. If the central derivations hold, the work provides valuable geometric insights into reconfigurable planar arrays by linking port placement to estimation performance via the inertia matrix. Strengths include the closed-form derivations, the invariance proofs, and the identification of the precision-ambiguity trade-off, all of which offer parameter-free characterizations that could guide practical design of fluid antenna systems beyond fixed geometries.

minor comments (3)
  1. [§III] §III: The derivation of the Rayleigh law for minimum inter-port distance is a key contribution, but the manuscript would benefit from an explicit comparison to the typical per-port nearest-neighbor distance (which scales differently) to avoid potential reader confusion with standard stochastic geometry results.
  2. [§IV] §IV, around the definition of the geometric inertia matrix: Provide a brief numerical example or small-M verification of the invariance to azimuth look direction to illustrate the proof.
  3. [Abstract and §V] Abstract and §V: The precision-ambiguity trade-off is conceptually important, but the discussion of increased spatial ambiguity would be strengthened by referencing a specific metric (e.g., peak sidelobe level or ambiguity function width) even if only qualitatively.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for the positive and accurate summary of our manuscript on finite-aperture planar fluid antenna arrays. The recommendation for minor revision is noted. No specific major comments or requested changes were provided in the report.

Circularity Check

0 steps flagged

Derivations self-contained from uniform random placement and standard array processing

full rationale

The paper's core results—the closed-form minimum inter-port distance distribution (claimed Rayleigh with O(M^{-1}) scaling), the 2×2 geometric inertia matrix parametrizing the CRB, its invariance to azimuth, and the precision-ambiguity trade-off—are derived analytically from the explicit assumption of uniform random port placement over the rectangular aperture together with standard Cramér-Rao bound expressions in array signal processing. No step reduces a claimed prediction to a fitted parameter by construction, no load-bearing premise rests solely on self-citation, and the matrix definition plus its eigenstructure properties are obtained directly from the position statistics without circular redefinition or smuggling of ansatzes. The scaling discrepancy with classical 2-D nearest-neighbor asymptotics is a potential correctness issue but does not constitute circularity in the derivation chain.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

Framework rests on the domain assumption of uniform random port placement over a rectangular aperture and standard far-field array signal models; no free parameters or new invented entities are introduced in the abstract.

axioms (1)
  • domain assumption Candidate ports are placed uniformly at random over the rectangular aperture
    Invoked to derive the minimum inter-port distance distribution and the geometric inertia matrix (abstract, first and second contributions)

pith-pipeline@v0.9.0 · 5821 in / 1345 out tokens · 52722 ms · 2026-05-22T04:23:42.764497+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Reference graph

Works this paper leans on

71 extracted references · 71 canonical work pages

  1. [1]

    Perf ormance limits of fluid antenna systems,

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

    work page 2020

  2. [2]

    Fluid antenna systems,

    K. K. Wong, A. Shojaeifard, K. F. Tong and Y . Zhang, “Fluid antenna systems,” IEEE Trans. Wireless Commun., vol. 20, no. 3, pp. 1950–1962, Mar. 2021

    work page 1950

  3. [3]

    Design and experimental validation of mmWave surface wave enabled fluid antennas for future wireless communicati ons,

    Y . Shen et al., “Design and experimental validation of mmWave surface wave enabled fluid antennas for future wireless communicati ons,” IEEE Antennas & Wireless Propag. Lett. , vol. 25, no. 4, pp. 1467–1471, Apr. 2026

    work page 2026

  4. [4]

    Electromagnetically reconfigurable fluid antenna system for wireless communications: Design, modeling, algorithm , fabrication, and experiment,

    R. Wang et al., “Electromagnetically reconfigurable fluid antenna system for wireless communications: Design, modeling, algorithm , fabrication, and experiment,” IEEE J. Sel. Areas Commun. , vol. 44, pp. 1464–1479, 2026

    work page 2026

  5. [5]

    Historical review of fluid antenna a nd movable antenna,

    L. Zhu and K. K. Wong, “Historical review of fluid antenna a nd movable antenna,” arXiv preprint, arXiv:2401.02362, 2024

    work page arXiv 2024

  6. [6]

    A review on reconfigurabl e liquid dielectric antennas,

    E. Motovilova, and S. Y . Huang, “A review on reconfigurabl e liquid dielectric antennas,” Materials (Basel) , vol. 13, no. 8, article number: 1863, pp. 1–28, Apr. 2020

    work page 2020

  7. [7]

    Fluid antenna systems enabled by reconfigurable holographic surfaces: Beamforming design and experimenta l validation,

    S. Zhang et al. , “Fluid antenna systems enabled by reconfigurable holographic surfaces: Beamforming design and experimenta l validation,” IEEE J. Select. Areas Commun. , vol. 44, pp. 1417–1431, 2026

    work page 2026

  8. [8]

    Pr o- grammable meta-fluid antenna for spatial multiplexing in fa st fluctuating radio channels,

    B. Liu, K.-F. Tong, K. K. Wong, C.-B. Chae, and H. Wong, “Pr o- grammable meta-fluid antenna for spatial multiplexing in fa st fluctuating radio channels,” Optics Express, vol. 33, no. 13, pp. 28898–28915, 2025

    work page 2025

  9. [9]

    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

    work page 2025

  10. [10]

    Wideban d pixel-based fluid antenna system: An antenna design for smar t city,

    B. Liu, T. Wu, K. K. Wong, H. Wong, and K. F. Tong, “Wideban d pixel-based fluid antenna system: An antenna design for smar t city,” IEEE Internet Things J. , vol. 13, no. 4, pp. 6850–6862, Feb. 2026

    work page 2026

  11. [11]

    Rec on- figurable pixel antennas meet fluid antenna systems: A paradi gm shift to electromagnetic signal and information processing,

    K. K. Wong, C. Wang, S. Shen, C.-B. Chae and R. Murch, “Rec on- figurable pixel antennas meet fluid antenna systems: A paradi gm shift to electromagnetic signal and information processing,” IEEE Wireless Commun., vol. 33, no. 1, pp. 191–198, Feb. 2026

    work page 2026

  12. [12]

    A tutorial on fluid antenna system for 6G networks: Encompassing communication theory, optimization methods and hard- ware designs,

    W. K. New et al. , “A tutorial on fluid antenna system for 6G networks: Encompassing communication theory, optimization methods and hard- ware designs,” IEEE Commun. Surv. & Tut. , vol. 27, no. 4, pp. 2325– 2377, Aug. 2025

    work page 2025

  13. [13]

    Fluid antennas: Reshaping intrinsic properties for flexible radiation characteristics in intelligent wireles s networks,

    W.-J. Lu et al. , “Fluid antennas: Reshaping intrinsic properties for flexible radiation characteristics in intelligent wireles s networks,” IEEE Commun. Mag. , vol. 63, no. 5, pp. 40–45, May 2025. 12

    work page 2025

  14. [14]

    A contemporary survey on fluid antenna systems: Fundamentals and networking perspectives,

    H. Hong et al. , “A contemporary survey on fluid antenna systems: Fundamentals and networking perspectives,” IEEE Trans. Netw. Sci. Eng., vol. 13, pp. 2305–2328, 2026

    work page 2026

  15. [15]

    Fluid antenna systems: Redefining reconfigurable wireless communications,

    W. K. New et al. , “Fluid antenna systems: Redefining reconfigurable wireless communications,” IEEE J. Sel. Areas Commun. , vol. 44, pp. 1013–1044, 2026

    work page 2026

  16. [16]

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

    T. Wu et al. , “Fluid antenna systems enabling 6G: Principles, applica- tions, and research directions,” to appear in IEEE Wireless Commun. , DOI:10.1109/MWC.2025.3629597, 2025

    work page doi:10.1109/mwc.2025.3629597 2025

  17. [18]

    A new anal ytical ap- proximation of the fluid antenna system channel,

    M. Khammassi, A. Kammoun, and M.-S. Alouini, “A new anal ytical ap- proximation of the fluid antenna system channel,” IEEE Trans. Wireless Commun., vol. 22, no. 12, pp. 8843–8858, Dec. 2023

    work page 2023

  18. [19]

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

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

    work page 2024

  19. [20]

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

    W. K. New, K. K. Wong, H. Xu, and K.-F. Tong, “Fluid antenn a system: New insights on outage probability and diversity gain,” IEEE Trans. Wireless Commun., vol. 23, no. 5, pp. 4846–4859, Jan. 2024

    work page 2024

  20. [21]

    Novel expressions for the outage probabili ty and diversity gains in fluid antenna system,

    J. D. V ega-S´ anchez, A. E. L ´ opez-Ram´ ırez, L. Urquiza -Aguiar, and D. P . M. Osorio, “Novel expressions for the outage probabili ty and diversity gains in fluid antenna system,” IEEE Wireless Commun. Lett. , vol. 13, no. 2, pp. 372–376, Feb. 2024

    work page 2024

  21. [22]

    On the performance of fluid antennas systems under α -µ fading channels,

    P . D. Alvim et al., “On the performance of fluid antennas systems under α -µ fading channels,” IEEE Wireless Commun. Lett. , vol. 13, no. 1, pp. 108–112, Jan. 2024

    work page 2024

  22. [23]

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

    F. Rostami Ghadi, K. K. Wong, F. Javier L ´ opez-Mart´ ıne z, and K. F. Tong, “Copula-based performance analysis for fluid ant enna systems under arbitrary fading channels,” IEEE Commun. Lett. , vol. 27, no. 11, pp. 3068–3072, Nov. 2023

    work page 2023

  23. [24]

    A Gaussian copula approach to the performance analysis of fluid antenna systems,

    F. Rostami Ghadi et al., “A Gaussian copula approach to the performance analysis of fluid antenna systems,” IEEE Trans. Wireless Commun. , vol. 23, no. 11, pp. 17573–17585, Nov. 2024

    work page 2024

  24. [25]

    An information-theoretic characterization of MIMO-FAS: Optimiza- tion, diversity-multiplexing tradeoff and q-outage capacity,

    W. K. New, K. K. Wong, H. Xu, K. F. Tong, and C.-B. Chae, “An information-theoretic characterization of MIMO-FAS: Optimiza- tion, diversity-multiplexing tradeoff and q-outage capacity,” IEEE Trans. Wireless Commun., vol. 23, no. 6, pp. 5541–5556, Jun. 2024

    work page 2024

  25. [26]

    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

    work page 2024

  26. [27]

    Successive Bayesian reconstructor for channel estimation in fluid antenna syste ms,

    Z. Zhang, J. Zhu, L. Dai, and R. W. Heath Jr., “Successive Bayesian reconstructor for channel estimation in fluid antenna syste ms,” IEEE Trans. Wireless Commun. , doi:10.1109/TWC.2024.3515135, 2024

    work page doi:10.1109/twc.2024.3515135 2024

  27. [28]

    Sparse Baye sian learning-based channel estimation for fluid antenna system s,

    B. Xu, Y . Chen, Q. Cui, X. Tao, and K. K. Wong, “Sparse Baye sian learning-based channel estimation for fluid antenna system s,” IEEE Wireless Commun. Lett. , vol. 14, no. 2, pp. 325–329, Feb. 2025

    work page 2025

  28. [29]

    FAS meets OFDM: Enabling wideband 5G NR,

    H. Hong et al., , “FAS meets OFDM: Enabling wideband 5G NR,” IEEE Trans. Commun., vol. 73, no. 11, pp. 12884–12898, Nov. 2025

    work page 2025

  29. [30]

    Downlink OFDM-FAMA in 5G-NR systems,

    H. Hong et al. , “Downlink OFDM-FAMA in 5G-NR systems,” IEEE Trans. Wireless Commun., vol. 24, no. 12, pp. 10116–10132, Dec. 2025

    work page 2025

  30. [31]

    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, Sept. 2024

    work page 2024

  31. [32]

    Fluid anten na-assisted ISAC systems,

    L. Zhou, J. Y ao, M. Jin, T. Wu, and K. K. Wong, “Fluid anten na-assisted ISAC systems,” IEEE Wireless Commun. Lett., vol. 13, no. 12, pp. 3533– 3537, Dec. 2024

    work page 2024

  32. [33]

    Shifting the ISAC trade-off with fluid antenna sys- tems,

    J. Zou et al. , “Shifting the ISAC trade-off with fluid antenna sys- tems,” IEEE Wireless Commun. Lett. , vol. 13, no. 12, pp. 3479–3483, Dec. 2024

    work page 2024

  33. [34]

    Integrated sensing and communication meets smart propaga tion engi- neering: Opportunities and challenges,

    K. Meng, C. Masouros, K. K. Wong, A. P . Petropulu and L. Ha nzo, “Integrated sensing and communication meets smart propaga tion engi- neering: Opportunities and challenges,” IEEE Netw., vol. 39, no. 2, pp. 278–285, Mar. 2025

    work page 2025

  34. [35]

    O n fundamental limits for fluid antenna-assisted integrated s ensing and communications for unsourced random access,

    Z. Zhang, K. K. Wong, J. Dang, Z. Zhang, and C.-B. Chae, “O n fundamental limits for fluid antenna-assisted integrated s ensing and communications for unsourced random access,” IEEE J. Select. Areas Commun., vol. 44, pp. 136–149, 2026

    work page 2026

  35. [36]

    Fluid reconfigurable intelligent surface (FRIS) enabling secure wireless com- munications,

    X. Zhu, K. K. Wong, B. Tang, W. Chen and C. -B. Chae, “Fluid reconfigurable intelligent surface (FRIS) enabling secure wireless com- munications,” IEEE Wireless Commun. Lett. , vol. 15, pp. 2408–2412, 2026

    work page 2026

  36. [37]

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

    F. Rostami Ghadi et al. , “Phase-mismatched STAR-RIS with FAS- assisted RSMA users,” IEEE Trans. on Commun. , vol. 74, pp. 2032– 2046, 2026

    work page 2032

  37. [38]

    Performance analysis of w ireless communication systems assisted by fluid reconfigurable inte lligent sur- faces,

    F. Rostami Ghadi, K. K. Wong, F. Javier L ´ opez-Mart´ ıne z, G. C. Alexandropoulos and C.-B. Chae, “Performance analysis of w ireless communication systems assisted by fluid reconfigurable inte lligent sur- faces,” IEEE Wireless Commun. Lett. , vol. 14, no. 12, pp. 3922–3926, Dec. 2025

    work page 2025

  38. [39]

    FIRES: Fluid integrated reflecting and emitting surfaces,

    F. Rostami Ghadi et al., “FIRES: Fluid integrated reflecting and emitting surfaces,” IEEE Wireless Commun. Lett., vol. 14, no. 11, pp. 3744–3748, Nov. 2025

    work page 2025

  39. [40]

    Fluid antenna enabling secret communications,

    B. Tang et al. , “Fluid antenna enabling secret communications,” IEEE Commun. Lett. , vol. 27, no. 6, pp. 1491–1495, Jun. 2023

    work page 2023

  40. [41]

    Coding-enhanced cooperative jamming for secret commu- nication in fluid antenna systems,

    H. Xu et al., “Coding-enhanced cooperative jamming for secret commu- nication in fluid antenna systems,” IEEE Commun. Lett. , vol. 28, no. 9, pp. 1991–1995, Sept. 2024

    work page 1991

  41. [42]

    Physical layer security over fluid antenna systems: Secrecy performance analysis,

    F. R. Ghadi et al. , “Physical layer security over fluid antenna systems: Secrecy performance analysis,” IEEE Trans. Wireless Commun., vol. 23, no. 12, pp. 18201–18213, Dec. 2024

    work page 2024

  42. [43]

    Fluid antenna system: S ecrecy outage probability analysis,

    J. D. V ega-S´ anchez, L. F. Urquiza-Aguiar, H. R. C. Mora , N. V . O. Garz´ on, and D. P . M. Osorio, “Fluid antenna system: S ecrecy outage probability analysis,” IEEE Trans. V eh. Technol., vol. 73, no. 8, pp. 11458–11469, Aug. 2024

    work page 2024

  43. [44]

    Cram´ er– Rao bounds for activity detection in conventional and fluid a ntenna sys- tems,

    Z. Zhang, K. K. Wong, H. Jiang, C. Masouros and C.-B. Chae , “Cram´ er– Rao bounds for activity detection in conventional and fluid a ntenna sys- tems,” IEEE Wireless Commun. Lett., DOI:10.1109/LWC.2026.3691385, 2026

    work page doi:10.1109/lwc.2026.3691385 2026

  44. [45]

    Joint activity detection and channel estimation for fluid antenna system exploiting geographical and angular inform ation,

    Z. Zhang et al., “Joint activity detection and channel estimation for fluid antenna system exploiting geographical and angular inform ation,” IEEE J. Sel. Topics Sig. Proc. , DOI:10.1109/JSTSP .2026.3673148, 2026

    work page doi:10.1109/jstsp 2026

  45. [46]

    On fundamental limits of slow-fluid antenna multiple access for unsourced random access,

    Z. Zhang et al. , “On fundamental limits of slow-fluid antenna multiple access for unsourced random access,” IEEE Wireless Commun. Lett. , vol. 14, no. 11, pp. 3455–3459, Nov. 2025

    work page 2025

  46. [47]

    Finite-blocklength fluid antenna systems,

    Z. Zhang et al. , “Finite-blocklength fluid antenna systems,” arXiv preprint, ariXiv2509.15643v2, 2026

    work page arXiv 2026

  47. [48]

    Finite-blocklength fluid antenna systems with spatial block-correlation channel model,

    Z. Zhang et al. , “Finite-blocklength fluid antenna systems with spatial block-correlation channel model,” IEEE Wireless Commun. Lett. , vol. 15, pp. 1911–1915, 2026

    work page 1911

  48. [49]

    Fluid antenna multiple access for 6G: A holistic review,

    H. Hong et al., “Fluid antenna multiple access for 6G: A holistic review,” IEEE Open J. Commun. Soc. , vol. 7, pp. 2607–2633, 2026

    work page 2026

  49. [50]

    Fluid antenna multiple acces s,

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

    work page 2022

  50. [51]

    Fast fluid a ntenna multiple access enabling massive connectivity,

    K. K. Wong, K.-F. Tong, Y . Chen, and Y . Zhang, “Fast fluid a ntenna multiple access enabling massive connectivity,” IEEE Commun. Lett. , vol. 27, no. 2, pp. 711–715, Feb. 2023

    work page 2023

  51. [52]

    Slow fluid antenna multiple access,

    K. K. Wong, D. Morales-Jimenez, K. F. Tong, and C.-B. Cha e, “Slow fluid antenna multiple access,” IEEE Trans. Commun. , vol. 71, no. 5, pp. 2831–2846, May 2023

    work page 2023

  52. [53]

    Cod ed fluid antenna multiple access over fast fading channels,

    H. Hong, K. K. Wong, K.-F. Tong, H. Shin and Y . Zhang, “Cod ed fluid antenna multiple access over fast fading channels,” IEEE Wireless Commun. Lett , vol. 14, no. 4, pp. 1249–1253, Apr. 2025

    work page 2025

  53. [54]

    5G-coded fluid antenna multiple access over block fading channels

    H. Hong, K. K. Wong, K.-F. Wong, H. Xu and H. Li, “5G-coded fluid antenna multiple access over block fading channels” Electron. Lett., vol. 61, no. 1, pp. e70166, Jan. 2025

    work page 2025

  54. [55]

    Turbocha rging fluid antenna multiple access,

    N. Waqar, K. K. Wong, C.-B. Chae, and R. Murch, “Turbocha rging fluid antenna multiple access,” IEEE Transactions on Wireless Communica- tions, vol. 25, pp. 4038–4052, 2026

    work page 2026

  55. [56]

    Attentio nal copula- aided turbo fluid antenna massive access,

    N. Waqar, K. K. Wong, C.-B. Chae, and R. Murch, “Attentio nal copula- aided turbo fluid antenna massive access,” IEEE Wireless Communica- tions Letters , vol. 15, pp. 1951–1955, 2026

    work page 1951

  56. [57]

    Compact ultra mas sive antenna array: A simple open-loop massive connectivity sch eme,

    K. K. Wong, C.-B. Chae and K.-F. Tong, “Compact ultra mas sive antenna array: A simple open-loop massive connectivity sch eme,” IEEE Trans. Wireless Commun. , vol. 23, no. 6, pp. 6279–6294, Jun. 2024

    work page 2024

  57. [58]

    CUMA uplink for interference-resilient multi-cell networks,

    C. Rao, K. K. Wong, Y . Zhang, and C.-B. Chae, “CUMA uplink for interference-resilient multi-cell networks,” IEEE Wireless Commun. Lett., vol. 15, pp. 2249–2253, 2026

    work page 2026

  58. [59]

    Optimizing t he spectral efficiency of multiuser MIMO smart antenna systems

    K. K. Wong, R. D. Murch, and K. Ben Letaief, “Optimizing t he spectral efficiency of multiuser MIMO smart antenna systems”, in Proc. IEEE Wireless Commun. Netw. Conf. (WCNC) , vol. 1, pp. 426–430, 23-28 Sept. 2000, Chicago, USA

    work page 2000

  59. [60]

    Performance en- hancement of multiuser MIMO wireless communication system s,

    K. K. Wong, R. D. Murch, and K. Ben Letaief, “Performance en- hancement of multiuser MIMO wireless communication system s,” IEEE Trans. Commun., vol. 50, no. 12, pp. 1960–1970, Dec. 2002

    work page 1960

  60. [61]

    A joint-chan nel diagonalization for multiuser MIMO antenna systems,

    K. K. Wong, R. D. Murch, and K. Ben Letaief, “A joint-chan nel diagonalization for multiuser MIMO antenna systems,” IEEE Trans. Wireless Commun., vol. 4, no. 2, pp. 773–786, Jul. 2003

    work page 2003

  61. [62]

    Efficient ODMA for unsourced random access in MIMO and hybrid massive MIMO,

    Z. Zhang et al. , “Efficient ODMA for unsourced random access in MIMO and hybrid massive MIMO,” IEEE Internet Things J. , vol. 11, no. 23, pp. 38846–38860, Dec. 2024. 13

    work page 2024

  62. [63]

    Fluid an tenna- enhanced flexible beamforming,

    J. Xu, Z. Zhang, J. Dang, H. Jiang, and Z. Zhang, “Fluid an tenna- enhanced flexible beamforming,” in Proc. IEEE Wireless Commun. Netw. Conf. (WCNC) , 13-16 Apr. 2026, Kuala Lumpur, Malaysia

    work page 2026

  63. [64]

    Finite-aperture fluid antenna array design: Analysis and algorithm,

    Z. Zhang et al. , “Finite-aperture fluid antenna array design: Analysis and algorithm,” IEEE Wireless Commun. Lett. , DOI:10.1109/LWC.2026.3685911, 2026

    work page doi:10.1109/lwc.2026.3685911 2026

  64. [65]

    Cram´ er–Rao bounds for coprime and other sparse arrays, which find more sources than sensors,

    C.-L. Liu and P . P . V aidyanathan, “Cram´ er–Rao bounds for coprime and other sparse arrays, which find more sources than sensors,” Digit. Signal Process., vol. 61, pp. 43–61, Feb. 2017

    work page 2017

  65. [66]

    Minimum-redundancy linear arrays,

    A. T. Moffet, “Minimum-redundancy linear arrays,” IEEE Trans. Anten- nas & Propag. , vol. 16, no. 2, pp. 172–175, Mar. 1968

    work page 1968

  66. [67]

    Two moments su ffice for Pois- son approximations: The Chen–Stein method,

    R. Arratia, L. Goldstein, and L. Gordon, “Two moments su ffice for Pois- son approximations: The Chen–Stein method,” Ann. Probab. , vol. 17, no. 1, pp. 9–25, Jan. 1989

    work page 1989

  67. [68]

    Stoica and R

    P . Stoica and R. Moses, Spectral Analysis of Signals . Prentice Hall, 2005

    work page 2005

  68. [69]

    S. M. Kay, Fundamentals of Statistical Signal Processing: Estimatio n Theory. Prentice Hall, 1993

    work page 1993

  69. [70]

    A review on array m utual coupling analysis,

    C. Craeye and D. Gonz´ alez-Ovejero, “A review on array m utual coupling analysis,” Radio Sci. , 2011

    work page 2011

  70. [71]

    Mutual coupling effects on CRB,

    H. Inanoglu and R. V accaro, “Mutual coupling effects on CRB,” in Proc. Asilomar, 2004

    work page 2004

  71. [72]

    Direction finding in the pr esence of mutual coupling,

    A. Friedlander and A. Weiss, “Direction finding in the pr esence of mutual coupling,” IEEE Trans. Antennas & Propag. , vol. 39, no. 3, pp. 273–284, Mar. 1991

    work page 1991