Near-Field Channel Estimation with ELAA Modular Arrays Under Hardware Impairments

Fuente: arXiv
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Autori principali: Demir, Özlem Tuğfe, Björnson, Emil
Natura: Preprint
Pubblicazione: 2025
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author Demir, Özlem Tuğfe
Björnson, Emil
author_facet Demir, Özlem Tuğfe
Björnson, Emil
contents Extremely large-scale antenna arrays (ELAAs) enable high spatial resolution and multiplexing, especially for user equipments (UEs) in the radiative near-field. To reduce hardware cost, modular ELAA architectures with distributed baseband units (BBUs) are gaining traction. This paper addresses near-field line-of-sight (LOS) channel estimation under low noise amplifier (LNA)-induced hardware impairments in such modular systems. We propose computationally efficient estimators that exploit the array geometry and constant-modulus structure of near-field LOS channels, including a novel two-dimensional (2D) discrete Fourier transform (DFT) masking technique that improves estimation accuracy and significantly reduces fronthaul signaling. Numerical results show that the proposed methods significantly outperform the conventional least squares (LS) method.
format Preprint
id arxiv_https___arxiv_org_abs_2509_16688
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Near-Field Channel Estimation with ELAA Modular Arrays Under Hardware Impairments
Demir, Özlem Tuğfe
Björnson, Emil
Signal Processing
Information Theory
Extremely large-scale antenna arrays (ELAAs) enable high spatial resolution and multiplexing, especially for user equipments (UEs) in the radiative near-field. To reduce hardware cost, modular ELAA architectures with distributed baseband units (BBUs) are gaining traction. This paper addresses near-field line-of-sight (LOS) channel estimation under low noise amplifier (LNA)-induced hardware impairments in such modular systems. We propose computationally efficient estimators that exploit the array geometry and constant-modulus structure of near-field LOS channels, including a novel two-dimensional (2D) discrete Fourier transform (DFT) masking technique that improves estimation accuracy and significantly reduces fronthaul signaling. Numerical results show that the proposed methods significantly outperform the conventional least squares (LS) method.
title Near-Field Channel Estimation with ELAA Modular Arrays Under Hardware Impairments
topic Signal Processing
Information Theory
url https://arxiv.org/abs/2509.16688