arXiv subjects

Kai-Kit Wong

Publications and source records attributed to Kai-Kit Wong.

At least 19 recordsLinked to original sources

arXiv2026

Robust Joint Beamforming and Configuration Design in FARIS-Aided Systems

In this paper, we propose a robust transmission design for multi-user systems assisted by a fluid active reconfigurable intelligent surface (FARIS), which enables both active reflection and dynamic port selection and thereby offers enhanced flexibility, under imperfect channel state information (CSI). We formulate a robust minimum sum-rate maximization problem by jointly optimizing the base station beamformer, the utilized FARIS coefficients, and the active element selection, while explicitly accounting for CSI errors and practical power constraints. The resulting problem is inherently nonconvex due to the coupled optimization variables and discrete port-selection structure. To tackle this challenge, we first reformulate the original problem via a weighted minimum mean square error (WMMSE) approach and then devise an alternating optimization (AO) framework, where each resulting subproblem admits efficient solutions and the overall algorithm converges to a stationary point. Simulation results demonstrate that the proposed robust FARIS scheme consistently outperforms conventional designs, highlighting the effectiveness of jointly leveraging degree-of-freedom (DoF) enhancement and active signal amplification under CSI uncertainty.

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arXiv2026

Enabling Secure Wireless Communications for FARIS-Aided Systems

This paper investigates secure downlink transmission assisted by a fluid active reconfigurable intelligent surface (FARIS), which enables both active reflection and dynamic port selection, offering enhanced flexibility for physical-layer security. We formulate a secrecy rate maximization problem that jointly optimizes the transmit beamformer, active reflection coefficients, and fluid port configuration under practical power constraints. To efficiently handle the resulting highly nonconvex problem, we develop a tailored alternating optimization (AO) framework that decomposes the original joint design into tractable subproblems, where each admits an efficient solution while preserving the system constraints, enabling an effective joint optimization of beamforming and FARIS reconfiguration. Numerical results demonstrate that the proposed FARIS-assisted design consistently outperforms the benchmarks. The results further highlight the robustness of FARIS against unfavorable eavesdropping geometries, confirming its potential as a powerful enabler for secure communications in challenging environments.

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arXiv2026

HARQ-CC-Aided Slow Fluid Antenna Multiple Access with Highly Correlated Ports: An LST-Based Performance Analysis

Hybrid automatic repeat request with chase combining (HARQ-CC) improves the reliability of slow fluid antenna multiple access (sFAMA) through multi-round combining. However, existing analysis has not fully utilized the structure of densely spaced and highly correlated fluid antenna system (FAS) ports to derive tractable per-round characterizations, thereby maintaining a computationally intensive process. This paper re-investigates downlink HARQ-CC-aided sFAMA with densely-spaced and highly-correlated FAS configuration. Under a spatial block correlation model, we first formulate two validity-corrected high-correlation approximations for the per-round selected-port signal-to-interference ratio (SIR) distribution and its Laplace--Stieltjes transform (LST): a Marcum-Q-kernel route and a lower-complexity step-threshold route. Closed-form expressions are also obtained for block-representative antenna selection (BR-AS) and fixed-position antenna (FPA). Then, the per-round characteristics are used to evaluate the multi-round accumulated-SIR distribution through SIR-domain Stieltjes convolution and numerical LST inversion, yielding the outage probability, average number of transmissions, and payload throughput. Numerical results show close agreement between the two evaluation methods. The analytical FAS results are conservative relative to simulation but preserve the performance trends and receiver ordering. The FAS receiver consistently outperforms the benchmarks, while the payload-throughput gain from increasing the HARQ transmission limit becomes marginal under severe multiuser interference.

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arXiv2026

Modeling and Performance Analysis for Fluid Antenna System Enabled UAV Near-Field Communications

Fluid antenna systems (FASs) offer a promising solution for unmanned aerial vehicle (UAV) air-to-ground (A2G) communications by enabling reconfigurable radiation characteristics. Addressing the limitations of traditional models in capturing the dynamic port configuration of FAS and the near-field nature of UAV communications, this paper proposes a dynamic port-reconfigurable near-field channel model for FAS-assisted UAV-to-mobile user (MU) links. Furthermore, we develop a FAS-adaptive subarray partition scheme utilizing a greedy strategy. By decomposing line-of-sight (LoS) and non-line-of-sight (NLoS) components and integrating UAV motion dynamics with FAS port activation states, the proposed model accurately characterizes the non-uniform spatial distribution of near-field channels. The subarray partition scheme dynamically groups active ports to satisfy near-field conditions while significantly reducing computational complexity, supported by a dynamic update algorithm that efficiently handles subarray adjustments during port switching. To avoid low effective gain and deep-fading ports in dense FAS configurations, a channel gain-based selection strategy is employed to prioritize high-gain ports. We derive and analyze the modeling accuracy and channel capacity, investigating the impact of FAS dimensions, port spacing, active port count, and UAV dynamics on system performance. Finally, the computational complexity of the subarray partition scheme is evaluated, verifying its advantages for real-time applications and providing a theoretical foundation for the design and analysis of FAS in dynamic scenarios.

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arXiv2026

CSI Reconstruction in Fluid Antenna Systems Without Spatial Covariance Priors

Fluid antenna systems (FASs) exploit many candidate ports for spatial diversity, but hardware constraints allow channel observations at only a few active ports. Whether full-port CSI can be recovered without pre-acquired channel statistics remains open. Under the Clarke isotropic scattering model, we show that the channel lies in a low-dimensional spatial modal subspace determined by the scattering environment rather than the total port count. Consequently, recovery becomes feasible when the number of observed ports reaches the modal dimension (i.e., $M\geq r$), even when $M\ll N$. We further establish a sharp feasibility threshold: reliable recovery is impossible below this dimension regardless of SNR, whereas accuracy improves with additional observations above it. By decomposing the recovery error into modal truncation, estimation, and learning components, we derive explicit tradeoffs among RF chains, pilot overhead, transmit power, and training data. These results enable scalable prior-free full-port CSI recovery with few active ports.

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arXiv2026

Semi-Blind Fluid Antenna System: Port Selection via Statistical Analysis

The fluid antenna system (FAS) enables position reconfigurability. A potential drawback of real-time FAS, however, is that it requires complete channel state information (CSI) for each FAS port at every communication time slot, an approach referred to as ideal-FAS. Recognizing the difficulties of achieving ideal-FAS, we propose a FAS scheme based on incomplete CSI, referred to as semi-blind FAS. This paper first introduces the spatial-temporal framework of FAS, upon which the proposed semi-blind FAS is developed. The proposed semi-blind FAS is lightweight and computationally efficient, scalable to an arbitrary number of ports and time slots, and operates without pre-training or deep learning structures. The scheme effectively exploits incomplete historical CSI to estimate the conditional distribution across all FAS ports at the desired time slot, thereby identifying the statistical optimal port for signal reception. Generally, the key idea of semi-blind FAS is to select the optimal port through conditional distribution analysis, from a statistical perspective, with optimality defined according to the scenario of interest. Inspired by information-theoretic entropy, we further develop the residual entropy power ratio to characterize how physical parameters influence the performance gap between semi-blind FAS and ideal-FAS. Our analysis reveals that estimation performance depends not only on the number of sampled ports and time slots, but also on the specific indices of ports with given CSI at each time slot, i.e., the port sampling strategy. This critical factor has been largely overlooked in existing port estimation studies. Numerical results demonstrate that the proposed semi-blind FAS achieves performance comparable to, and in some cases indistinguishable from, that of ideal-FAS, while requiring significantly fewer port CSI measurements and lower port switching speeds.

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arXiv2026

Learned Blockwise Port Activation for Real Time Beamforming in Fluid Antenna Arrays

Fluid antenna arrays (FAAs), support multiuser downlink transmission by activating a subset of reconfigurable ports. The activation mask jointly determines the effective channel and the sparse radiating aperture, which requires a balance among sum rate, sidelobe suppression, hardware constraints, and online complexity. Channel driven selection can cluster active ports and increase sidelobes, whereas sidelobe oriented synthesis is typically channel independent and can sacrifice sum rate. This paper proposes learned blockwise port activation (L-BPA), for real time sidelobe aware FAA downlink beamforming. L-BPA activates a fixed number of ports in each aperture block, which supports grouped switching hardware and limits port clustering. A lightweight convolutional network scores ports using multiuser channel features, port coordinates, and user power statistics. Training combines blockwise straight through masks with a differentiable peak sidelobe level (PSLL), surrogate. During inference, learned scores are combined with multiscale geometric repulsion, followed by regularized zero forcing precoding over the reduced effective channel. L-BPA reduces the average PSLL by 3.26 dB relative to uniform sparse activation while achieving a slightly higher sum rate. It also reduces the PSLL by 8.13 dB and 10.10 dB relative to greedy and gain based selection, respectively, without iterative online search.

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arXiv2026

JEPA-CFM: A Joint Embedding Predictive Architecture-based Channel Foundation Model for Robust Fluid Antenna Systems

Fluid antenna systems (FAS) have emerged as a promising technology for sixth-generation (6G) wireless networks. By allowing antenna elements to move freely within a compact region, FAS can exploit rich spatial diversity without additional hardware. However, acquiring real-time channel state information (CSI), extrapolating channel values to unmeasured antenna ports, and determining accurate user positions remain major obstacles. These challenges stem mainly from strong spatial correlations within the limited aperture and the scarcity of observable data. To overcome these limitations, this paper introduces joint embedding predictive architecture (JEPA)-based channel foundation model (CFM) specifically designed for FAS. The model adopts JEPA to learn versatile representations by extracting high-level latent embeddings of masked or unobserved channel segments. Unlike conventional approaches that attempt pixel-by-pixel reconstruction of raw CSI coefficients, JEPA-CFM focuses on predicting abstract structures in a compact feature space. The pre-training objective combines three complementary loss terms: the standard masked autoencoder reconstruction loss, the JEPA latent prediction loss, and a sliced isotropic Gaussian regularization (SIGReg) term. Together, these components prevent representation collapse and significantly enhance robustness under severe spatial correlation and highly sparse observations. After pre-training, the encoder is frozen, and lightweight task-specific heads are attached: a decoder for channel extrapolation and a global average pooling layer followed by a multi-layer perceptron regression head for wireless positioning. Extensive simulations in the realistic DeepMIMO urban scenario demonstrate that JEPA-CFM substantially outperforms the conventional masked autoencoder baseline in channel extrapolation and wireless positioning.

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arXiv2026

HARQ for Slow Fluid Antenna Multiple Access

Slow fluid antenna multiple access (sFAMA), enabled by the fluid antenna system (FAS), has recently emerged as a practical and low-complexity paradigm for supporting massive wireless connectivity. While existing studies have characterized its physical-layer performance under one-shot transmission, its interaction with retransmission protocols and the resulting networking performance remain largely unexplored. In this paper, we study a downlink hybrid automatic repeat request (HARQ)-assisted sFAMA framework, termed HARQ-sFAMA, in which each user performs distinguished port selection in every HARQ round and combines the received signals across multiple rounds to improve decoding reliability. We develop a comprehensive analytical framework to characterize the outage probability, average packet waiting time, and energy efficiency of the proposed system. The analysis reveals how HARQ exploits the spatial reconfigurability of FAS to simultaneously enhance reliability and improve queueing performance. Numerical results corroborate the theoretical analysis and demonstrate that the HARQ-sFAMA system significantly outperforms conventional one-shot sFAMA in terms of reliability, delay, and energy efficiency. These findings suggest that the integration of HARQ and sFAMA provides a promising pathway toward a practical and standards-compatible massive access solution for future wireless networks.

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arXiv2026

Performance Limits of FRIS Systems in Nakagami-$m$ Fading

Fluid reconfigurable intelligent surfaces (FRIS) have recently emerged as a promising technology for enhancing wireless link reliability through spatial decorrelation. However, their performance analysis remains challenging due to the sum-product structure of the cascaded channel. This letter develops a rigorous analytical framework for FRIS-assisted wireless systems over arbitrarily correlated Nakagami-$m$ fading channels. Specifically, we introduce a physically consistent correlation model for Nakagami-$m$ fading and derive tractable statistical characterizations for the cascaded channel. These results lead to rigorous lower bounds for the outage probability (OP), with a simplified expression also obtained for the independent and identically distributed case. To the best of our knowledge, these are the first strict OP lower bounds reported for an FRIS-aided wireless system under arbitrarily correlated Nakagami-$m$ fading. CLT- and Gamma-based approximations are included as benchmark methods. Notably, the numerical results show that the proposed OP bound not only provides rigorous performance guarantees but also yields a noticeably tighter OP characterization than the CLT approximation in the high-SNR regime.

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arXiv2026

Dual Fluid Antenna-Assisted UAV MIMO Networks

Fluid Antennas (FAs)-assisted Unmanned Aerial Vehicle (UAV) networks leverage the FA position adaptivity and flexible beamforming to overcome the limitations of Fixed-Positioned Antennas (FPAs) in dynamic UAV channels and Multi-User (MU) interference. This letter investigates a dual FA-assisted UAV network for MU-Multiple-Input-Multiple-Output (MIMO) downlink communications, aiming to maximize the average achievable rate through the joint optimization of UAV trajectory, the transmit/receive FA positions, and beamforming. The formulated problem is highly coupled and non-convex. Accordingly, an efficient Alternating Optimization (AO)-based algorithm is developed for decomposed subproblems, yielding a suboptimal solution. Numerical results demonstrate significant performance gains of 120% and 110% over conventional FPA-based and existing FA-based baselines, respectively.

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arXiv2026

A Survey of Physical-layer Authentication Enhanced by Emerging Spatial Domain Technologies

This article surveys spatial-domain-enhanced Physical-layer Authentication (PLA), with Dual-polarized Antennas (DPA), Massive Multiple-Input Multiple-Output (MIMO), and Reconfigurable Intelligent Surfaces (RIS) as the primary focus. With the rapid growth of wireless deployments, authentication mechanisms face stringent requirements for high security, low overhead, and low latency. PLA offers lightweight identity verification by exploiting physical-layer characteristics. However, the effectiveness of PLA critically depends on how physical observations are constructed and validated under wireless channels. Unlike existing surveys that mainly organize PLA by authentication modality, feature source, and evaluation metrics, this work emphasizes the connection between spatial-domain enhancement mechanisms, the resulting feature representation, and the authentication procedure. We review how DPA, Massive MIMO, and RIS reshape PLA feature representation, and we summarize newly introduced security threats along with representative defense strategies. Case studies further illustrate the practical impact, such as representative detection-probability trends across Signal-to-Noise Ratio regimes and quantitative comparisons among representative schemes. Finally, we outline promising future opportunities enabled by Dynamic Metasurface Antennas, Extra-large MIMO, and spatial configuration with artificial intelligence.

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arXiv2026

Enormous Fluid Antenna Systems (E-FAS) for Wireless Sensing: Channel Modeling and Conditional Estimation Limits

In this paper, we develop a fundamental analytical framework for integrated sensing and communications (ISAC) enabled by the Enormous Fluid Antenna System (E-FAS), which transforms a collection of coordinated intelligent surfaces into a gigantic reconfigurable electromagnetic aperture, with particular emphasis on the limits of angular sensing.We begin by developing a bidirectional sensing channel model that explicitly captures the complete sensing process, including surface-wave (SW) routing, distributed reradiation, target scattering, and echo propagation. Based on this channel model, we formulate a parametric observation model for target sensing and derive the associated Fisher information matrix (FIM) and Cramer-Rao bound (CRB) for angular estimation. The analysis demonstrates that E-FAS gives rise to a fundamentally different sensing regime compared with conventional array-based and reconfigurable-surface-aided ISAC architectures. Our analysis uncovers that maximizing coherent routing gain does not necessarily maximize sensing performance, exposing a fundamental trade-off between SW routing gain and sensing diversity in programmable propagation environments. Numerical results validate the developed framework and demonstrate that E-FAS-enabled ISAC systems can achieve substantial angular sensing gains over conventional architectures under the same transmit-power budget. The results further underscore the importance of jointly optimizing propagation routing and sensing functionality, positioning E-FAS as a new paradigm for ISAC.

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arXiv2026

Spatial Modulation for Tx-SIMO-FAS: Port Selection and Performance Analysis

This paper considers a single-input multiple-output (SIMO) setup with a fluid antenna system (FAS) at the transmitter side and multiple fixed antennas at the receiver, which is referred to as a Tx-SIMO-FAS. We investigate the use of spatial modulation (SM) utilizing the FAS on a single radio-frequency (RF) chain while the receiver side performs maximum-likelihood detection. Unlike conventional antenna arrays, however, the large number of fluid antenna ports accommodated within a limited aperture introduces strong spatial correlation, which reduces the distinguishability of port indices and degrades the reliability of index detection. To address this challenge, three correlation-aware port-selection schemes are proposed: successive fluid Euclidean-distance-optimized selection (SF-EDAS), successive orthogonal port selection (SOPS), and correlation-constrained orthogonal array selection (CC-COAS). These schemes focus on enhancing received-constellation separation, improving channel-basis conditioning, and jointly optimizing channel gain and inter-port decorrelation, respectively. To understand the performance limits of FAS-SM, a reliability analysis is developed by decomposing the channel into an energy-based degree of freedom (DoF), and an extreme-value DoF. High signal-to-noise ratio (SNR) analysis reveals an effective diversity order determined by the number of selected ports, the number of receive antennas, and the energy-based spatial DoF. Furthermore, the aperture-limited array gain is characterized through a scalar equivalent independent-look approximation involving the Digamma function. Numerical results demonstrate that the proposed schemes significantly outperform conventional SM and grouping-based benchmarks. Among them, CC-COAS achieves the most favorable tradeoff between error performance and computational complexity.

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arXiv2026

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

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.

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arXiv2026

Enhanced Fluid Index Modulation for Integrated Data and Energy Transfer

Integrated data and energy transfer (IDET) is a promising technique for supporting sustainable low-power wireless networks. To improve both communication reliability and energy transfer efficiency, this paper investigates a fluid index modulation (FIM) assisted IDET system, where the base station employs a two-dimensional fluid antenna system (FAS) and the receiver adopts a power-splitting architecture. In FIM, the information bits are delivered not only from the modulation symbols, but also the index of antenna position. Under finite-alphabet signaling, the average harvested power, bit error rate (BER), and achievable data rate are derived in closed form. A joint optimization problem is formulated to maximize the average harvested power subject to BER and achievable rate constraints by jointly optimizing the port selection, precoding vector, and power splitting ratio. An alternating optimization framework is developed, where the precoding vector and port selection are obtained via a Riemannian augmented Lagrangian method (RALM) and block coordinate descent (BCD) algorithm, respectively. Simulation results demonstrate that the proposed scheme achieves a superior rate-energy trade-off over benchmark schemes, while the proposed algorithm attains near-optimal performance with significantly lower complexity than exhaustive search.

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arXiv2026

Geometry-Structured Channel Reconstruction for Conventional and Fluid Antenna Systems: Bayesian Inference and Fundamental Limits

Accurate channel state information (CSI) acquisition is critical for exploiting the spatial flexibility of fluid antenna systems (FASs). However, port selection and transmission optimization require CSI over a large number of candidate port positions, making direct port-wise estimation prohibitively costly in terms of pilot overhead. This paper addresses this challenge through geometry-structured channel reconstruction, which exploits the fact that the port-domain CSI can be parameterized by a small number of dominant propagation paths. We first establish fundamental mean square error (MSE) and normalized MSE (NMSE) benchmarks for both geometry-structured and unstructured channel reconstruction, providing analytical references for evaluating the intrinsic benefit of geometric modeling in conventional antenna systems and FASs. Motivated by the strong spatial correlation induced by densely distributed fluid antenna ports, we further propose a Bayesian reconstruction framework, termed geometry-structured expectation-maximization approximate message passing (GS-EM-AMP). The proposed algorithm incorporates geometric channel structure into the EM-AMP procedure and adaptively learns unknown statistical parameters from noisy observations. Numerical results demonstrate that GS-EM-AMP achieves near-bound reconstruction accuracy while maintaining strong robustness against steering-domain correlation, thereby offering an efficient and reliable solution for large-scale CSI acquisition in FASs.

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arXiv2026

Stochastic Geometry Analysis of Uplink CUMA-Enabled Cellular Networks

Uplink cellular networks are interference-dominated but interference channel state information (CSI) is rarely available at scale. The emerging fluid antenna system (FAS) concept, which provides additional spatial degrees of freedom through multi-port reconfiguration, offers a promising alternative to CSI-intensive multi-antenna processing. Building on this concept, compact ultra-massive arrays (CUMA) exploit large-scale port selection with low implementation complexity. In each uplink transmission, CUMA activates a subset of ports based on only the desired-link CSI and combines the selected ports via simple superposition, yielding coherent enhancement of the desired user signal, while inter-cell interference aggregates largely non-coherently due to the random superposition effect. Consequently, CUMA is well suited to multi-cell uplink scenarios where CSI is limited. In this paper, we analyze uplink CUMA in multi-cell cellular networks using a stochastic geometry framework. We derive a tight approximate expression for the signal-to-interference ratio (SIR) coverage probability, and further characterize the average user rate and cell sum-rate. The analysis quantifies how key design parameters impact performance and reveals the scaling behavior with network densification. Simulation results validate the accuracy of the derived expressions and show that uplink CUMA achieves competitive, and often superior, performance relative to conventional schemes under practical CSI constraints, highlighting its potential as a low-complexity, hardware-efficient uplink solution for future large-scale cellular networks.

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