DFT-Based Channel Estimation for Holographic MIMO

TL;DR

This paper introduces a low-complexity DFT-based channel estimation method for holographic MIMO systems that maintains optimal performance with reduced computational effort and increased robustness.

Contribution

It proposes a novel DFT approximation approach for MMSE channel estimation in holographic MIMO, reducing complexity from N^3 to N log N and improving robustness.

Findings

Achieves MMSE performance with significantly lower computational load.

Scales as N log N, suitable for large arrays.

Offers increased robustness to covariance matrix imperfections.

Abstract

Holographic MIMO (hMIMO) systems with a massive number of individually controlled antennas N make minimum mean square error (MMSE) channel estimation particularly challenging, due to its computational complexity that scales as $N^3$ . This paper investigates uniform linear arrays and proposes a low-complexity method based on the discrete Fourier transform (DFT) approximation, which follows from replacing the covariance matrix by a suitable circulant matrix. Numerical results show that, already for arrays with moderate size (in the order of tens of wavelengths), it achieves the same performance of the optimal MMSE, but with a significant lower computational load that scales as $N \log N$. Interestingly, the proposed method provides also increased robustness in case of imperfect knowledge of the covariance matrix.