A Novel Framework for the Characterization of Continuous Electromagnetic Manifolds

TL;DR

This paper introduces a comprehensive framework for characterizing electromagnetic manifolds in MIMO systems, improving modeling accuracy and flexibility over existing methods, validated through MATLAB simulations.

Contribution

It presents a unified, high-accuracy EM manifold modeling approach that overcomes key limitations of prior discrete models and extends to arbitrary array geometries.

Findings

Enhanced near-field modeling accuracy with Gauss-Legendre quadrature.

Validation confirms improved accuracy over state-of-the-art methods.

Framework supports optimization over infinite-dimensional feeding functions.

Abstract

A unified framework for the characterization of continuous electromagnetic (EM) manifolds for arbitrary multipleinput multiple-output (MIMO) system geometries is presented. The EM manifold refers to the set of all physically realizable radiated field vectors, parameterized by the array excitation, that encodes the full spatial structure of the antenna system including near-field phase variations, polarization, and mutual coupling. Building upon the discrete moment-matrix formulation, the proposed framework addresses three fundamental limitations simultaneously: (i) point-source near-field modeling errors in the radiation operator; (ii) confinement of the beamforming space to the $N$-dimensional subspace dictated by hardware port count; and (iii) restriction to linear (1D) array geometries. Each mesh element is modeled as a two-dimensional (2D) planar patch, whose spatially averaged Green's function is evaluated via Gauss-Legendre (GL) quadrature, yielding superior nearfield accuracy at negligible additional cost. A continuous feeding function $w(\mathbf{p})\in L^2(\mathcal{S}_\mathrm{T})$ is introduced as the infinite-dimensional limit of the $N$-port network, enabling optimization over a higher dimensional current subspace, decoupled from hardware constraints. Full-wave MATLAB Antenna Toolbox validation confirms near-field accuracy improvements over the state-of-the-art (SotA) baseline for both linear and planar array geometries, while maintaining reasonable computational complexity.