EM-Based Channel Estimation for mMIMO LEO SATCOM Under Imperfect Doppler Compensation

TL;DR

This paper introduces an EM-based data-aided channel estimation method for mMIMO LEO SATCOM systems that effectively handles imperfect Doppler compensation caused by user mobility, improving accuracy in highly time-varying channels.

Contribution

It proposes a novel EM algorithm combined with DLP-BEM for robust channel estimation under imperfect Doppler compensation in LEO satellite communications.

Findings

Outperforms existing methods in normalized mean square error

Achieves lower symbol error rate

Effectively mitigates channel aging effects

Abstract

Massive multiple-input multiple-output low-Earth-orbit communication channels are highly time-varying due to severe Doppler shifts and propagation delays. While satellite-mobility-induced Doppler shifts can be compensated using known ephemeris data, those caused by user mobility require accurate user positioning information; the absence of such information contributes to amplified channel aging in conventional channel estimators. To address this challenge, we propose a data-aided channel estimator based on the expectation-maximization (EM) algorithm, combined with a discrete Legendre polynomial basis expansion model (DLP-BEM), to estimate the channel under imperfect Doppler compensation. The EM algorithm iteratively exploits hidden data symbols for improved channel estimation, while DLP-BEM regularizes the process by projecting the channel estimate onto a lower-dimensional subspace that mitigates estimation errors. Simulation results demonstrate the superiority of the proposed framework over existing methods in terms of normalized mean square error and symbol error rate.