arXiv subjects

Zhaolin Wang

Publications and source records attributed to Zhaolin Wang.

At least 37 records · Page 2Linked to original sources

arXiv2026

Mutual Coupling-Aware Beamforming in Multi-User Continuous Aperture Array Systems

A mutual coupling-aware beamforming design for continuous aperture array (CAPA)-aided multi-user systems is investigated. First, a transmit coupling kernel is characterized to explicitly capture the mutual coupling effects inherent in CAPAs, based on which a mutual coupling-aware sum-rate maximization functional optimization problem is formulated. To address this problem, a kernel approximation (KA)-based weighted minimum mean-squared error (WMMSE) algorithm is developed. The optimal beamforming condition is derived within the WMMSE framework using the calculus of variations, while KA is employed to obtain a closed-form beamforming solution via wavenumber-domain Fourier transforms and Gauss-Legendre quadrature. Furthermore, the proposed framework is extended to CAPA-to-CAPA multiple-input multiple-output (MIMO) systems. Finally, numerical results demonstrate that: 1) the proposed algorithm achieves improved performance compared to benchmark schemes; 2) the modeled coupling effects are physically rational, where the performance of spatially discrete arrays converges to that of CAPAs; and 3) CAPA-to-CAPA MIMO systems can achieve higher degrees of freedom when the transceivers are placed in close proximity.

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arXiv2026

1-bit Quantized Continuous Aperture Arrays

Continuous aperture arrays (CAPAs) have emerged as a promising physical-layer paradigm for sixth generation (6G) systems, offering spatial degrees of freedom beyond those of conventional discrete antenna arrays. This paper investigates the interaction between the CAPA receive architecture and low-cost 1-bit analog-to-digital converters (ADCs), which impose a severe nonlinear distortion penalty in conventional discrete systems. For Rayleigh fading, we derive a moment matching approximation (MMA)-based closed-form symbol error probability (SEP) approximation based on Gamma moment-matching of the spatial eigenvalue distribution, and show that CAPAs incur a diversity-order penalty governed by Jensen's inequality on the mode eigenvalues. For line-of-sight (LoS) propagation, we prove that CAPA achieves exactly the unquantized additive white Gaussian noise (AWGN) performance bound under perfect spatial and phase alignment, completely eliminating the 1-bit penalty that forces discrete systems to double their antenna count. Monte Carlo simulations under Rayleigh, Rician, and LoS conditions validate all analytical results.

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arXiv2026

Wideband Near-Field Sensing in ISAC: Unified Algorithm Design and Decoupled Effect Analysis

To advance integrated sensing and communications (ISAC) in sixth-generation (6G) extremely large-scale multiple-input multiple-output (XL-MIMO) networks, a low-complexity compressed sensing (CS)-based dictionary design is proposed for wideband near-field (WB-NF) target localization. Currently, the massive signal dimensions in the WB-NF regime impose severe computational burdens and high spatial-frequency coherence on conventional grid-based algorithms. Furthermore, a unified framework exploiting both wideband (WB) and near-field (NF) effects is lacking, and the analytical conditions for simplifying this model into decoupled approximations remain uncharacterized. To address these challenges, the proposed algorithm mathematically decouples the mutual coherence function and introduces a novel angle-distance sampling grid with customized distance adjustments, drastically reducing dictionary dimensions while ensuring low coherence. To isolate the individual WB and NF impacts, two coherence-based metrics are formulated to establish the effective boundaries of the narrowband near-field (NB-NF) and wideband far-field (WB-FF) regions, where respective multiple signal classification (MUSIC) algorithms are utilized. Simulations demonstrate that the CS-based method achieves robust performance across the entire regime, and the established boundaries provide crucial theoretical guidelines for WB and NF effect decoupling.

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arXiv2026

Extended-Target Classification and Localization for Near-Field ISAC

Near-field integrated sensing and communication (ISAC) enables object-level sensing from distance-dependent array responses, yet most existing near-field methods still rely on point-target models and realistic extended targets remain largely unexplored. In this paper, joint target classification and range-azimuth localization are studied from channel responses of realistic extended targets. A dual-branch inference framework is proposed. Semantic and geometric branches are used for classification and localization, respectively. Cross-task attention is introduced after task-specific encoding so that complementary cues can be exchanged without forcing full feature sharing from the input stage. To improve localization on the same backbone, uncertainty-aware regression and a physics-guided structured objective are adopted, including planar consistency, peak-response regularization, and geometry-coupling constraints. Training and evaluation data are generated from full-wave electromagnetic scattering simulations of voxelized vehicle targets with randomized heading angles, material contrasts, and placements. The compared variants show that cross-task attention mainly benefits classification, while uncertainty-aware and structured supervision are needed to recover strong localization performance on the same backbone. Under the adopted shared-OFDM benchmark, the proposed framework reaches the best joint operating point with fewer sensing tones for the same target performance region.

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arXiv2026

A Spatio-Temporal-Frequency Transformer Framework for Near-Field Target Recognition

A target recognition framework relying on near-field integrated sensing and communication (ISAC) systems is proposed. By exploiting the distance-dependent spatial signatures provided by the near-field spherical wavefront, high-accuracy sensing is realized in a bandwidth-efficient manner. A spatio--temporal--frequency (STF) transformer framework is introduced for target recognition using electromagnetic features found in the wireless channel response. In particular, a lightweight spatial encoder is employed to extract features from the antenna array for each frame and subcarrier. These features are then fused by a time-frequency transformer head with positional embeddings to model temporal dynamics and cross-subcarrier correlations. Simulation results demonstrate that strong target recognition performance can be achieved even with limited bandwidth resources.

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arXiv2026

Exploiting Segmented Waveguide-Enabled Pinching-Antenna Systems (SWANs) for Uplink Tri-Hybrid Beamforming

A segmented waveguide-enabled pinching-antenna system (SWAN)-based tri-hybrid beamforming architecture is proposed for uplink multi-user MIMO communications, which jointly optimizes digital, analog, and pinching beamforming. Both fully-connected (FC) and partially-connected (PC) structures between RF chains and segment feed points are considered. For the FC architecture, tri-hybrid beamforming is optimized using the weighted minimum mean-square error (WMMSE) and zero-forcing (ZF) approaches. Specifically, the digital, analog, and pinching beamforming components are optimized via a closed-form solution, Riemannian manifold optimization, and a Gauss-Seidel search, respectively. For the PC architecture, an interleaved topology tailored to the SWAN receiver is proposed, in which segments assigned to each RF chain (sub-array) are interleaved with those from other sub-arrays. Based on this structure, a WMMSE-based tri-hybrid design is developed, in which the Riemannian-manifold update used for the FC structure is replaced by element-wise phase calibration to exploit sparsity in analog beamforming. To gain insight into the performance of the proposed system, the rate-scaling laws with respect to the number of segments are derived for both the FC and PC structures. Our results demonstrate that: i)~SWAN with the proposed tri-hybrid beamforming consistently outperforms conventional hybrid beamforming and conventional pinching-antenna systems with pinching beamforming for both the FC and PC structures; and ii)~the PC structure can strike a good balance between sum rate and energy consumption when the number of segments is large; and iii) the achievable rate does not necessarily increase with the number of segments.

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arXiv2026

Failure Detection for Pinching-Antenna Systems

A signal processing-based framework is proposed for detecting random segment failures in segmented waveguide-enabled pinching-antenna systems. To decouple the passively combined uplink signal and to provide per-segment observability, tagged pilots are employed. A simple tag is attached to each segment and is used to apply a known low-rate modulation at the segment feed, which assigns a unique signature to each segment. Based on the tagged-pilot model, a low-complexity per-segment maximum-likelihood (ML) detector is developed for the case in which the pilot length is no smaller than the number of segments. For the case in which the pilot length is smaller than the number of segments, sparsity in the failure-indicator vector is exploited and a compressive sensing-based detector is adopted. Numerical results show that the per-segment detector approaches joint ML performance, while the compressive sensing-based detector achieves reliable detection with a short pilot and can outperform baselines that require much longer pilots.

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arXiv2026

Generative Site-Specific Beamforming via Information-Maximizing Codebook

A novel generative site-specific beamforming (GenSSBF) framework is proposed, which integrates a site-information-maximizing (SIM) codebook with a conditional flow matching (CFM)-based beam generator. By this framework, the site-specific radio propagation environment is learned at the base station (BS), enabling the generation of high fidelity communication beams from coarse reference-signal-received-power (RSRP) feedback provided by user equipments (UEs). In the proposed design, a low-dimensional SIM probing codebook is first constructed by maximizing the mutual information between the RSRP feedback and the site-specific channel. This design not only reduces the initial beam sweeping overhead, but also enhances the amount of channel state information conveyed through UE feedback. By treating the RSRP feedback as a conditional prior, a CFM-based generative model is further developed to explicitly capture the uncertainty in beam generation. Specifically, a small set of UE-specific candidate beams is generated by inferring the learned generative model and sampling from the corresponding posterior distribution, after which the final data transmission beam is selected by the UE. Extensive simulation results demonstrate the effectiveness of both the proposed SIM codebook and the CFM-based beam generator. The proposed GenSSBF framework achieves beamforming performance nearly identical to maximum ratio transmission while requiring only eight probing beams and eight candidate beams.

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arXiv2026

On the Maintainability of Pinching-Antenna Systems: A Failure-Repair Perspective

The pinching-antenna system (PASS) enables wireless channel reconfiguration through optimized placement of pinching antennas along dielectric waveguides. In this article, a unified analytical framework is proposed to characterize the maintainability of PASS. Within this framework, random waveguide failures and repairs are modeled by treating the waveguide lifetime and repair time as exponentially distributed random variables, which are characterized by the failure rate and the repair rate, respectively. The operational state of the waveguide is described by a two-state continuous-time Markov chain, for which the transition probabilities and steady-state probabilities of the waveguide being working or failed are analyzed. By incorporating the randomness of the waveguide operational state into the transmission rate, system maintainability is characterized using the probability of non-zero rate (PNR) and outage probability (OP). The proposed framework is applied to both a conventional PASS employing a single long waveguide and a segmented waveguide-enabled pinching-antenna system (SWAN) composed of multiple short waveguide segments under two operational protocols: segment switching (SS) and segment aggregation (SA). Closed-form expressions for the PNR and OP are derived for both architectures, and the corresponding scaling laws are analyzed with respect to the service-region size and the number of segments. It is proven that both SS-based and SA-based SWAN achieve higher PNR and lower OP than conventional PASS, which confirms the maintainability advantage of segmentation. Numerical results demonstrate that: i) the maintainability gain of SWAN over conventional PASS increases with the number of segments, and ii) SA provides stronger maintainability than SS.

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arXiv2026

Pinching-Antenna Systems (PASS): A Tutorial

Pinching antenna systems (PASS) present a breakthrough among the flexible-antenna technologies, and distinguish themselves by facilitating large-scale antenna reconfiguration, line-of-sight creation, scalable implementation, and near-field benefits, thus bringing wireless communications from the last mile to the last meter. A comprehensive tutorial is presented in this paper. First, the fundamentals of PASS are discussed, including PASS signal models, hardware models, power radiation models, and pinching antenna activation methods. Building upon this, the information-theoretic capacity limits achieved by PASS are characterized, and several typical performance metrics of PASS-based communications are analyzed to demonstrate its superiority over conventional antenna technologies. Next, the pinching beamforming design is investigated. The corresponding power scaling law is first characterized. For the joint transmit and pinching design in the general multiple-waveguide case, 1) a pair of transmission strategies is proposed for PASS-based single-user communications to validate the superiority of PASS, namely sub-connected and fully connected structures; and 2) three practical protocols are proposed for facilitating PASS-based multi-user communications, namely waveguide switching, waveguide division, and waveguide multiplexing. A possible implementation of PASS in wideband communications is further highlighted. Moreover, the channel state information acquisition in PASS is elaborated with a pair of promising solutions. To overcome the high complexity and suboptimality inherent in conventional convex-optimization-based approaches, machine-learning-based methods for operating PASS are also explored, focusing on selected deep neural network architectures and training algorithms. Finally, several promising applications of PASS in next-generation wireless networks are highlighted.

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arXiv2026

Beam-Brainstorm: A Generative Site-Specific Beamforming Approach

Accurately understanding the propagation environment is a fundamental challenge in site-specific beamforming (SSBF). This paper proposes a novel generative SSBF (GenSSBF) solution, which represents a paradigm shift from conventional unstructured prediction to joint-structure modeling. First, considering the fundamental differences between beam generation and conventional image synthesis, a unified GenSSBF framework is proposed, which includes a site profile, a wireless prompting module, and a generator. Second, a beam-brainstorm (BBS) solution is proposed as an instantiation of this GenSSBF framework. Specifically, the site profile is configured by transforming channel data from spatial domain to a reversible latent space via discrete Fourier transform (DFT). To facilitate practical deployment, the wireless prompt is constructed from the reference signal received power (RSRP) measured using a small number of DFT-beams. Finally, the generator is developed using a customized conditional diffusion model. Rather than relying on a meticulously designed global codebook, BBS directly generates diverse and high-fidelity user-specific beams guided by the wireless prompts. Simulation results on accurate ray-tracing datasets demonstrate that BBS can achieve near-optimal beamforming gain while drastically reducing the beam sweeping overhead, even in low signal-to-noise ratio (SNR) environments.

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arXiv2026

Generative Site-Specific Beamforming for Next-Generation Spatial Intelligence

This article proposes generative site-specific beamforming (GenSSBF) for next-generation spatial intelligence in wireless networks. Site-specific beamforming (SSBF) has emerged as a promising paradigm to mitigate the channel acquisition bottleneck in multiantenna systems by exploiting environmental priors. However, classical SSBF based on discriminative deep learning struggles: 1) to properly represent the inherent multimodality of wireless propagation and 2) to effectively capture the structural features of beamformers. In contrast, by leveraging conditional generative models, GenSSBF addresses these issues via learning a conditional distribution over feasible beamformers. By doing so, the synthesis of diverse and high-fidelity beam candidates from coarse channel sensing measurements can be guaranteed. This article presents the fundamentals, system designs, and implementation methods of GenSSBF. Case studies in both indoor and outdoor scenarios show that GenSSBF attains near-optimal beamforming gain with ultra-low channel acquisition overhead. Finally, several open research problems are highlighted.

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arXiv2025

Segmented Waveguide-Enabled Pinching-Antenna Systems (SWANs) for ISAC

A segmented waveguide-enabled pinching-antenna system (SWAN)-assisted integrated sensing and communications (ISAC) framework is proposed. Unlike conventional pinching antenna systems (PASS), which use a single long waveguide, SWAN divides the waveguide into multiple short segments, each with a dedicated feed point. Thanks to the segmented structure, SWAN enhances sensing performance by significantly simplifying the reception model and reducing the in-waveguide propagation loss. To balance performance and complexity, three segment controlling protocols are proposed for the transceivers, namely i) \emph{segment selection} to select a single segment for signal transceiving, ii) \emph{segment aggregation} to aggregate signals from all segments using a single RF chain, and iii) \emph{segment multiplexing} to jointly process the signals from all segments using individual RF chains. The theoretical sensing performance limit is first analyzed for different protocols, unveiling how the sensing performance gain of SWAN scales with the number of segments. Based on this performance limit, the Pareto fronts of sensing and communication performance are characterized for the simple one-user one-target case, which is then extended to the general multi-user single-target case based on time-division multiple access (TDMA). Numerical results are presented to verify the correctness of the derivations and the effectiveness of the proposed algorithms, which jointly confirm the advantages of SWAN-assisted ISAC.

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arXiv2025

Optimal Waveform Design for Continuous Aperture Array (CAPA)-aided ISAC Systems

A novel continuous-aperture-array (CAPA)-aided integrated sensing and communication (ISAC) framework is proposed. Specifically, an optimal continuous ISAC waveform is designed to form a directive beampattern for multi-target sensing while suppressing the multi-user interference (MUI). To achieve the goal of optimal waveform design, the directional beampattern of CAPA is first derived based on Green's function, whereafter a reference sensing waveform is obtained through wavenumber-domain optimization. Based on the reference sensing waveform, a weighted functional programming on the tradeoff between sensing beampattern mismatch and MUI is formulated. To solve the resulting problem, an optimal CAPA-ISAC waveform structure is analytically derived using a Lagrangian-transformation and calculus-of-variations method, where the Lagrangian multiplier associated with the optimal waveform structure is determined via Bisection search. The obtained optimal waveform reveals that it is concurrently affected by the reference sensing waveform, the channel correlations and the channel-symbol correlations. Finally, numerical results validate the effectiveness of the proposed system and waveform design, demonstrating that CAPA can achieve significant performance gains against the ISAC designs based on conventional spatially discrete array in both sensing accuracy and communication reliability.

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arXiv2025

Tri-Hybrid Beamforming Design for Fully-Connected Pinching Antenna Systems

A novel fully-connected (FC) tri-hybrid beamforming (THB) architecture is proposed for pinching antenna systems (PASS). In contrast to conventional sub-connected (SC) PASS, the proposed FC architecture employs a tunable phase-shifter network to interconnect all radio frequency (RF) chains with all waveguides. This facilitates a THB framework that integrates conventional hybrid analog-digital beamforming with pinching beamforming. A weighted sum-rate (WSR) optimization problem is then formulated to jointly optimize the transmit beamformers and pinching antenna (PA) positions. Two algorithms are developed to address this challenging non-convex problem. 1) Fractional programming (FP)-based algorithm: This algorithm directly maximizes the WSR using an FP-based alternating optimization framework. Particularly, a success-history based adaptive differential evolution (SHADE) method is proposed to optimize PA positions, effectively addressing the intractable multimodal objective function. 2) Zero-forcing (ZF)-based algorithm: To reduce design complexity, zero-forcing is employed for transmit beamforming. The PA positions are subsequently optimized to maximize the WSR via a modified SHADE method. Simulation results validate the effectiveness of the proposed algorithms, revealing that the FC-THB PASS achieves WSR comparable to the SC architecture while delivering superior energy efficiency with fewer RF chains.

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arXiv2025

Integration of Navigation and Remote Sensing in LEO Satellite Constellations

Low earth orbit (LEO) satellite constellations are becoming a cornerstone of next-generation satellite networks, enabling worldwide high-precision navigation and high-quality remote sensing. This paper proposes a novel dual-function LEO satellite constellation frame structure that effectively integrating navigation and remote sensing. Then, the Cramer-Rao bound (CRB)-based positioning, velocity measurement, and timing (PVT) error and the signal-to-ambiguity-interference-noise ratio (SAINR) are derived as performance metrics for navigation and remote sensing, respectively. Based on it, a joint beamforming design is proposed by minimizing the average weighted PVT error for navigation user equipments (UEs) while ensuring SAINR requirement for remote sensing. Simulation results validate the proposed multi-satellite cooperative beamforming design, demonstrating its effectiveness as an integrated solution for next-generation multi-function LEO satellite constellations.

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arXiv2025

Flexible Continuous Aperture Arrays

A novel electromagnetic (EM) structure termed flexible continuous aperture array (FCAPA) is proposed, which incorporates inherent surface flexibility into typical continuous aperture array (CAPA) systems, thereby enhancing the degrees-of-freedom (DoF) of multiple-input multiple-output (MIMO) systems equipped with this technology. By formulating and solving a downlink multi-user beamforming optimization problem to maximize the weighted sum rate (WSR) of the multiple users with FCAPA, it is shown that the proposed structure outperforms typical CAPA systems by a wide margin, with performance increasing with increasing morphability.

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arXiv2025

Cramér-Rao Bound Optimization for Near-Field Sensing with Continuous-Aperture Arrays

A Cramér-Rao bound (CRB) optimization framework for near-field sensing (NISE) with continuous-aperture arrays (CAPAs) is proposed. In contrast to conventional spatially discrete arrays (SPDAs), CAPAs emit electromagnetic (EM) probing signals through continuous source currents for target sensing, thereby exploiting the full spatial degrees of freedom (DoFs). The maximum likelihood estimation (MLE) method for estimating target locations in the near-field region is developed. To evaluate the NISE performance with CAPAs, the CRB for estimating target locations is derived based on continuous transmit and receive array responses of CAPAs. Subsequently, a CRB minimization problem is formulated to optimize the continuous source current of CAPAs. This results in a non-convex, integral-based functional optimization problem. To address this challenge, the optimal structure of the source current is derived and proven to be spanned by a series of basis functions determined by the system geometry. To solve the CRB minimization problem, a low-complexity subspace manifold gradient descent (SMGD) method is proposed, leveraging the derived optimal structure of the source current. Our simulation results validate the effectiveness of the proposed SMGD method and further demonstrate that i)~the proposed SMGD method can effectively solve the CRB minimization problem with reduced computational complexity, and ii)~CAPA achieves a tenfold improvement in sensing performance compared to its SPDA counterpart, due to full exploitation of spatial DoFs.

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