electromagnetic coupling modeling

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 neglect of antenna mutual coupling in existing metasurface-inspired large intelligent reflecting surface (MiLAC)-assisted MIMO research, which leads to model inaccuracies. Building upon multiport network theory, this work develops a physically consistent end-to-end MiLAC-MIMO model and proposes a mutual coupling-aware optimization framework to maximize received power. It is the first to reveal that mutual coupling inherently provides an averaging gain in MiLAC systems, demonstrating that such systems achieve performance equivalent to digital architectures equipped with impedance matching networks—yet require fewer RF chains—and consistently outperform configurations without matching networks. By leveraging convex optimization and closed-form solutions, the paper derives three analytical performance bounds, which are validated through extensive simulations.

This work addresses the challenge of enhancing wireless communication performance while simultaneously reducing the number of radio frequency (RF) chains and active antennas. To this end, the authors propose a mechanical beamforming architecture based on a three-dimensional passively coupled rotatable coupler. The system operates without additional RF chains; leveraging multiport circuit theory, they formulate a channel model and cast the coupler rotation optimization as a constrained non-convex problem. An efficient solution is achieved by integrating a spherical cap conditional gradient algorithm with the cross-entropy method. Simulation results demonstrate that the proposed approach significantly outperforms existing benchmarks in terms of received signal-to-noise ratio and overall communication performance, all while substantially lowering hardware complexity.

Existing multi-RIS-aided MIMO channel models neglect critical physical effects—including structural scattering, impedance mismatch, and unit-cell mutual coupling—leading to severe overestimation of channel gain (e.g., optimized performance of a four-RIS system reaches only 7% of its true physical limit). Method: This work establishes the first physically consistent multi-RIS channel model by rigorously integrating structural scattering, port impedance matching, and array mutual coupling, grounded in multi-port network theory and electromagnetic scattering modeling; it further derives the fundamental scaling law of channel gain. Contribution/Results: Numerical electromagnetic simulations validate that model error grows significantly with increasing RIS count and multipath richness, and conventional models fail entirely in multi-hop scenarios. Our model provides the first physics-based benchmark for multi-RIS system design, correcting a long-standing model mismatch in wireless communications.

This work addresses beyond-diagonal reconfigurable intelligent surfaces (BD-RIS) with mutual coupling, for which no rigorous global optimization framework accounting for coupling effects existed. Method: We establish the first mutual-coupling-aware global optimization theory, proposing a closed-form solution via matrix eigenanalysis and complex-domain optimization to maximize channel gain under fully connected and tree-connected architectures. Contribution/Results: We theoretically reveal that mutual coupling can enhance average channel gain in Rayleigh fading—refuting the common misconception that coupling is inherently detrimental—and derive a closed-form expression and scaling law for the maximum achievable gain with coupling. Both architectures are proven to share an identical theoretical gain upper bound. Mutual-coupling-agnostic optimization incurs up to 5 dB performance loss. Our results provide the first rigorous theoretical foundation for BD-RIS modeling, design, and deployment.

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.

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.

This study addresses the high complexity and cost of conventional active array beamforming by proposing a low-power alternative based on a flexible coupler-based antenna architecture. The design enables mechanical beam steering through physical displacement of passive coupling elements alone, modulating induced currents without requiring any adjustment to active antennas. This approach pioneers purely passive element repositioning for beam control, substantially reducing both hardware cost and power consumption. Leveraging multi-port circuit theory, the authors develop line-of-sight and multipath channel models and employ a block coordinate conditional gradient algorithm to optimize coupler placement. Experimental results demonstrate that, despite significantly fewer active elements and RF chains, the proposed system achieves notably higher spectral efficiency compared to existing benchmark schemes.

This work addresses the lack of systematic channel modeling for molecular communication in large-scale vascular networks, particularly concerning multipath effects. Building upon the closed-form MIGHT channel model, it introduces key wireless communication multipath metrics—such as RMS delay spread, mean excess delay, and coherence bandwidth—into vascular molecular communication for the first time. The study derives closed-form expressions for the channel frequency response and power delay profile, and integrates Poisson noise modeling to design a coherent decision-feedback detector. This approach effectively mitigates inter-symbol interference and enables performance evaluation across diverse vascular network topologies, offering theoretical guidance for critical system parameters including symbol duration, sampling instants, and detector memory length.

This study addresses the challenge of simultaneously mitigating severe path loss and maximizing spectral efficiency in millimeter-wave and terahertz communications. To this end, it proposes the first full-wave electromagnetic modeling framework that integrates multimodal propagation with polarization awareness, uniquely unifying polarization states and multimodal characteristics within a single physical model. This formulation reveals the intrinsic trade-offs among waveguide attenuation, atmospheric absorption, and geometric spreading. Building upon this model, the authors develop a closed-form polarization update algorithm and a modular optimization strategy to enable accurate modeling and efficient deployment of near-user antenna systems. Experimental results demonstrate that the proposed approach achieves up to a 167% improvement in spectral efficiency over single-mode systems, with polarization awareness alone contributing a 23% gain in aggregate data rate.