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Yuanhui Wu

Publications and source records attributed to Yuanhui Wu.

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UAV Fluid-Antenna Channel Acquisition under Intra-Scan Channel Aging

Sequential sounding in UAV fluid-antenna systems (FASs) provides additional spatial information but delays transmission, causing earlier channel observations to age. This paper addresses the resulting information--freshness tradeoff by jointly determining where to probe and when to stop under blockwise hardware constraints. A dynamic Karhunen--Loève estimator aligns asynchronous measurements with the transmission state, covariance information gain selects feasible probe locations, and an age-discount identity with a local one-more-slot condition characterizes the covariance-level balance between information and freshness. Paired simulations show that temporal alignment recovers most of the lower-tail reliability lost by static stacking, covariance-aware probing ranks highest numerically among the evaluated policies, and optimized one-slot sounding becomes statistically competitive with two-slot alternatives at the highest tested mobility. Within the evaluated schedule family, increasing mobility shifts the competitive operating region toward shorter scans, supporting joint probe-placement and sounding-duration design.

cs.IT

Impedance-Aware Zonal Port Activation for Fluid Antenna Arrays

Fluid antenna array (FAA) activation jointly determines the effective multi-user channel for precoding and the sparse physical aperture. Channel-oriented selection can concentrate high-gain ports and erode aperture quality, whereas geometry-oriented selection does not adapt to instantaneous channel state information (CSI). This paper formulates finite-port FAA activation as a rate--aperture--feasibility problem under an exact RF-chain budget. We propose impedance-aware zonal port activation (IA-ZPA), which couples compact CSI-conditioned port scoring with a checkerboard feasibility projection and inference-time mutual-impedance-aware selection. The learned scorer ranks ports, while the deterministic rule fixes the active aperture; a separate current-domain RZF backend then evaluates source-drive feasibility. Under a common induced-EMF protocol, IA-ZPA attains the largest constrained rate among the methods satisfying the prescribed mean-PSLL target with a substantially lower decision time than greedy selection.

cs.IT

EM-Guided Graph Learning for Fluid Antenna Beamforming under Current-Domain Constraints

Fluid antenna arrays (FAAs) reconfigure a finite set of radiating ports within a prescribed aperture. In compact apertures, however, channel-driven placement may cluster ports, strengthen mutual coupling, degrade radiation conditioning, increase source-voltage demand, and produce uneven current loading. This paper studies downlink multi-user beamforming with jointly optimized port placement and current-domain transmission. An electromagnetic-guided graph network predicts port layouts from channel observations and refines them using geometric and mutual-impedance information. The training objective jointly considers communication performance and electromagnetic feasibility, while a common evaluation procedure is applied to all methods. The results show that, under a common feasibility standard, the proposed method provides a controllable tradeoff among communication rate, current loading, and configuration latency.

cs.IT

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.

cs.IT

Electromagnetic-Aware Fluid Antenna Array

Fluid antenna arrays (FAAs) offer a promising means of exploiting spatial degrees of freedom through adaptive port positioning. However, most existing communication models treat antenna ports as independent channel samples and therefore overlook the electromagnetic coupling that fundamentally governs compact apertures. This paper develops an electromagnetic-aware current-domain framework for planar FAAs. The proposed model integrates position-dependent multiport impedance, mutual coupling, radiated and accepted power, source-voltage feasibility, and channel variations into a unified baseband-compatible description. The framework is implementation-agnostic: the closed-form half-wave-dipole model adopted in this paper is only one instance and can be replaced by full-wave, measured, or surrogate impedance and embedded-pattern models. Building on this framework, we formulate two optimization-oriented design problems. The first addresses single-beam superdirective beamforming through the joint optimization of port currents and positions under sidelobe, current, voltage, and geometry constraints. The second maximizes the multi-user weighted sum rate via current-domain precoding and position optimization under accepted-power, current, voltage, and spacing constraints. In both cases, the electromagnetic model is not applied as an after-design correction, but is incorporated directly into tractable alternating algorithms with convex current or precoding subproblems and reduced-gradient geometry updates. Simulation results demonstrate that, when properly modeled, mutual coupling can be exploited as a valuable design resource, enabling lower sidelobes and persistent sum-rate gains over fixed-grid and random fluid-antenna benchmarks.

cs.IT

Peak Sidelobe Suppression in Planar Fluid Antenna Array

Fluid antenna systems (FAS) have emerged as a promising technology for next-generation wireless communications, offering inherent reconfigurability and spatial adaptability. A distinctive and practically consequential property of fluid antenna arrays (FAAs) is their geometric diversity: by dynamically activating different subsets of spatially distributed ports across a dense discrete grid, a FAA can reconfigure its effective aperture geometry on demand, thereby unlocking unprecedented spatial degrees of freedom for radiation pattern synthesis. Exploiting such geometric flexibility, this paper investigates peak sidelobe level (PSLL) minimization in sparse planar FAAs through enhanced heuristic optimization. Specifically, an improved genetic algorithm (IGA) is proposed to determine the optimal port activation pattern that minimizes the PSLL under strict sparsity constraints. The proposed IGA incorporates tournament selection, adaptive operator probabilities, a hybrid crossover scheme, multi-point mutation, and an elite-pool preservation strategy to improve both convergence speed and solution quality. Simulation results demonstrate that the IGA significantly outperforms the canonical GA (CGA) in convergence behavior and final PSLL performance, achieving a 4.45 dB reduction in sidelobe levels while maintaining a comparable mainlobe width.

cs.IT

Jointly Correlated Dual-Side Fluid Antenna System

Fluid antenna systems (FASs) have introduced a new paradigm for wireless system design by revealing how mutual correlation can be exploited to harvest inherent spatial diversity. While existing studies have mainly focused on one-sided FAS configurations, i.e., with FAS deployed at either the transmitter or the receiver, this work investigates the ergodic capacity of a jointly correlated dual-side FAS under statistical eigenmode transmission. Specifically, a jointly correlated dual-side channel model is developed, and the corresponding ergodic capacity together with a tight closed-form upper bound is derived. In addition, the optimal power allocation is studied, and a practical iterative algorithm is proposed for its implementation.

cs.IT