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Parametric Near-Field MMSE Channel Estimation for sub-THz XL-MIMO Systems

2025/04/14 by Wen-Xuan Long, Long, Wen-Xuan, Marco Moretti +7 · 1 citation
Engineering · #Advanced MIMO Systems Optimization #Antenna Design and Analysis #Energy Harvesting in Wireless Networks #FOS: Electrical engineering #Signal Processing (eess.SP) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2504.10064

openalex publication_date 2025/04/14 · openalex created_date 2025/10/14 · openalex updated_date 2026/07/28

Abstract

Accurate channel estimation is essential for reliable communication in sub-THz extremely large (XL) MIMO systems. Deploying XL-MIMO in high-frequency bands not only increases the number of antennas, but also fundamentally alters channel propagation characteristics, placing the user equipments (UE) in the radiative near-field of the base station. This paper proposes a parametric estimation method using the multiple signal classification (MUSIC) algorithm to extract UE location data from uplink pilot signals. These parameters are used to reconstruct the spatial correlation matrix, followed by an approximation of the minimum mean square error (MMSE) channel estimator. Numerical results show that the proposed method outperforms the least-squares (LS) estimator in terms of the normalized mean-square error (NMSE), even without prior UE location knowledge.

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