model electromagnetic coupling

Conventional half-wavelength spacing decoupling criteria fail for continuous-aperture phased arrays (CAPAs) due to polarization-induced anisotropic mutual coupling. Method: We propose a continuous-domain mutual coupling model incorporating both polarization effects and surface losses, revealing the polarization-driven directional dependence of coupling. A functional optimization framework is formulated via variational calculus; the coupling kernel is approximated in the wavenumber domain using Gaussian–Legendre quadrature, and the resulting equivalent quadratic optimization problem is solved via conjugate gradient descent—generalized to discrete arrays. Contribution/Results: Analytical solutions for optimal array gain and beam patterns are derived in the large-aperture limit. Numerical validation confirms that discrete-array performance under the proposed coupled model converges to the continuous-aperture limit, whereas conventional uncoupled models violate physical consistency. Coupled-beam synthesis achieves enhanced directivity and polarization-dependent gain, establishing a new paradigm for high-density array design.

Conventional Rician channel models for ultra-wideband (UWB) MIMO communications suffer from physical inconsistency and limited bandwidth validity due to unmodeled antenna mutual coupling. Method: This paper proposes the first physically consistent wideband Rician channel modeling framework, embedding circuit theory into the standard MIMO channel representation. It jointly models antenna port impedances, mutual coupling networks, and propagation paths, explicitly characterizing how mutual coupling distorts the amplitude and phase of the line-of-sight (LOS) component—and its frequency dependence. Contributions/Results: First, it reveals that tight coupling reduces spatial correlation at lower frequencies. Second, it quantifies mutual-coupling-induced beamforming performance deviation. Third, it demonstrates a significant bandwidth broadening effect enabled by the new model. The framework provides an interpretable, scalable, physics-based foundation for UWB MIMO system design, channel estimation, and beam optimization.

This study addresses the significant degradation of beamforming performance in continuous-aperture arrays caused by electromagnetic mutual coupling, a challenge exacerbated by the high computational complexity and low solution efficiency of existing methods when incorporating accurate coupling models. Building upon a physically consistent mutual coupling model, the authors formulate beamforming design as a functional optimization problem and characterize its optimality conditions via a Fredholm integral equation. To solve this efficiently, they propose two strategies: a coordinate-transform-based kernel approximation that preserves operator structure while reducing discretization dimensionality, and a direct solver combining Nyström discretization with LU decomposition, augmented by offline factorization to enable stable and scalable large-scale optimization. Experiments demonstrate that the proposed approaches substantially reduce computational cost while maintaining accuracy, with the LU-based solver exhibiting exceptional efficiency and scalability in large-scale scenarios.

This work addresses the challenges in compact-aperture fluid antenna arrays, where channel-driven port placement often leads to port clustering, exacerbated mutual coupling, and uneven current loading. To overcome these issues, the authors propose an electromagnetically guided graph neural network framework that, for the first time, integrates electromagnetic constraints—such as mutual impedance and geometric layout—into graph-based learning. This approach jointly optimizes port configuration and current-domain beamforming strategies under a unified electromagnetic feasibility criterion. By doing so, it enables a controllable trade-off among communication rate, current distribution uniformity, and configuration latency, thereby significantly enhancing the overall performance of multiuser downlink transmissions.

This work addresses the common oversight of electromagnetic coupling in compact fluid antenna array designs, which often leads to inaccurate performance predictions. The authors propose an electromagnetic-aware current-domain modeling framework that unifies position-dependent multi-port impedances, mutual coupling, radiated/received power, source voltage constraints, and channel dynamics, explicitly embedding coupling effects into the optimization process as a usable design degree of freedom. Leveraging a closed-form half-wave dipole model—compatible with full-wave simulations or measured data—the method employs an alternating optimization strategy to jointly solve a convex current subproblem and a non-convex geometric update. Simulations demonstrate that the approach significantly suppresses sidelobes in single-beam superdirective beamforming and consistently enhances weighted sum rates in multi-user scenarios, outperforming fixed-grid and random fluid antenna baselines.

This study investigates the validity of the unidirectional approximation—neglecting the electromagnetic back-reaction from the receiver on the transmitter—in near-field non-line-of-sight (NLoS) propagation scenarios involving large-scale linear antenna arrays. Leveraging multiport communication theory, electromagnetic reciprocity, large-array modeling, and statistical averaging techniques, the work theoretically demonstrates for the first time that, in the asymptotic regime where the number of antennas tends to infinity, the unidirectional approximation holds in a mean-square sense. This result applies universally to both discrete arrays with fixed inter-element spacing and continuous apertures with fixed physical size. The findings provide rigorous theoretical justification for the physically consistent application of Rayleigh fading models in near-field wireless systems.

Existing channel models struggle to accurately capture the impact of antenna configurations on signal propagation in reconfigurable antenna systems, often neglecting polarization effects or relying on oversimplified assumptions. This work proposes a general electromagnetic channel model based on spherical vector wave expansion (SVWE), which, for the first time, fully incorporates antenna position, orientation, and polarization effects, rendering it applicable to a wide range of reconfigurable antennas. The model is rigorously derived from electromagnetic field theory and validated against commercial simulation software, demonstrating excellent predictive accuracy. Experimental results further reveal that dynamically optimizing antenna orientation can enhance communication rates by up to 70% compared to fixed configurations.

Conventional discrete array models struggle to accurately characterize the channel and signal properties of large-scale, high-density, high-frequency reconfigurable electromagnetic aperture systems. This work proposes a continuous-space modeling paradigm that unifies the representation of channels, signals, and beamformers as continuous fields and operators governed by Maxwell’s equations, thereby effecting a fundamental shift from discrete to continuous formulations. By integrating electromagnetics with information theory and leveraging wavenumber-domain analysis, functional analysis, and compressive sensing, the study reveals the intrinsic degrees of freedom and capacity limits of continuous apertures and develops finite-dimensional equivalent methods capable of handling infinite-dimensional problems. These contributions establish a theoretical foundation, provide essential analytical tools, and outline practical hardware implementation pathways for future wireless systems.

This work addresses the common oversight in existing reconfigurable antenna systems that neglect mutual coupling, thereby missing its potential to enhance channel capacity. For the first time, mutual coupling is treated not as an impairment but as a designable mechanism for performance improvement. The paper develops a unified joint optimization framework for both narrowband and wideband MIMO systems, actively exploiting mutual coupling–induced superdirectivity through coordinated optimization of antenna positions and beamforming. To this end, it introduces a circuit-theory–based mutual coupling matrix design, a unified antenna placement strategy suitable for wideband scenarios, and integrates block coordinate ascent, a Sylvester equation–based trust-region algorithm, and subcarrier joint optimization techniques. Extensive simulations under diverse channel conditions demonstrate that the proposed approach significantly improves system capacity and sum rate, confirming the effectiveness and superiority of deliberately harnessing mutual coupling.