Exploiting Mutual Coupling Characteristics for Channel Estimation in Holographic MIMO

TL;DR

This paper investigates how mutual coupling affects channel estimation in holographic MIMO systems, highlighting the importance of modeling these effects for accurate performance and proposing insights for designing efficient estimators.

Contribution

It provides a detailed analysis of mutual coupling's impact on channel estimation and emphasizes the need to incorporate these characteristics into estimation algorithms for holographic MIMO.

Findings

Neglecting mutual coupling degrades MMSE estimator performance.

Least-squares estimator is robust to mutual coupling at high SNR.

Understanding mutual coupling is crucial for practical holographic MIMO deployment.

Abstract

Holographic multiple-input multiple-output (MIMO) systems represent a spatially constrained MIMO architecture with a massive number of antennas with small antenna spacing as a close approximation of a spatially continuous electromagnetic aperture. Accurate channel modeling is essential for realizing the full potential of this technology. In this paper, we investigate the impact of mutual coupling and spatial channel correlation on the estimation precision in holographic MIMO systems, as well as the importance of knowing their characteristics. We demonstrate that neglecting mutual coupling can lead to significant performance degradation for the minimum mean squared error estimator, emphasizing its critical consideration when designing estimation algorithms. Conversely, the least-squares estimator is resilient to mutual coupling but only yields good performance in high signal-to-noise ratio regimes. Our findings provide insights into how to design efficient estimation algorithms in holographic MIMO systems, aiding its practical implementation.