A Universal Framework for Holographic MIMO Sensing

TL;DR

This paper introduces a universal framework for identifying the sensing space of arbitrarily shaped holographic MIMO antennas, enabling accurate estimation of spatial degrees of freedom and applicability to real-world conformal antennas.

Contribution

It presents a novel, extendable eigenvalue-based method to determine sensing spaces for any antenna shape, advancing beyond prior geometry-specific analyses.

Findings

Precisely estimates degrees of freedom for known geometries

Verifies applicability to conformal, real-world antennas

Provides a generic eigenvalue problem for sensing space analysis

Abstract

This paper addresses the sensing space identification of arbitrarily shaped continuous antennas. In the context of holographic multiple-input multiple-output (MIMO), a.k.a. large intelligent surfaces, these antennas offer benefits such as super-directivity and near-field operability. The sensing space reveals two key aspects: (a) its dimension specifies the maximally achievable spatial degrees of freedom (DoFs), and (b) the finite basis spanning this space accurately describes the sampled field. Earlier studies focus on specific geometries, bringing forth the need for extendable analysis to real-world conformal antennas. Thus, we introduce a universal framework to determine the antenna sensing space, regardless of its shape. The findings underscore both spatial and spectral concentration of sampled fields to define a generic eigenvalue problem of Slepian concentration. Results show that this approach precisely estimates the DoFs of well-known geometries, and verify its flexible extension to conformal antennas.