Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/11866
Title: Spatial Correlation Modeling and RS-LS Estimation of Near-Field Channels with Uniform Planar Arrays
Authors: Demir O.T.
Kosasih A.
Bjornson E.
Keywords: Extremely large-scale MIMO
near-field channels
reduced-subspace least-square estimator
spatial correlation
Channel estimation
Communication channels (information theory)
Image segmentation
Least squares approximations
Channel modelling
Extremely large-scale MIMO
Large-scales
Least-square estimators
LS-estimation
Near Field Channel
Planar arrays
Reduced-subspace least-square estimator
Spatial correlation models
Spatial correlations
5G mobile communication systems
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: Extremely large aperture arrays (ELAAs) can offer massive spatial multiplexing gains in the radiative near-field region in beyond 5G systems. While near-field channel modeling for uniform linear arrays has been extensively explored in the literature, uniform planar arrays - despite their advantageous form factor - have been somewhat neglected due to their more complex nature. Spatial correlation is crucial for non-line-of-sight channel modeling. Unlike far-field scenarios, the spatial correlation properties of near-field channels have not been thoroughly investigated. In this paper, we start from the fundamentals and develop a near-field spatial correlation model for arbitrary spatial scattering functions. Furthermore, we derive the lower-dimensional subspace where the channel vectors can exist. It is based on prior knowledge of the three-dimensional coverage region where scattering clusters exists and we derive a tractable one-dimensional integral expression. This subspace is subsequently employed in the reduced-subspace least squares (RSLS) estimation method for near-field channels, thereby enhancing performance over the traditional least squares estimator without the need for having full spatial correlation matrix knowledge. © 2024 IEEE.
Description: Huawei
25th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2024 -- 10 September 2024 through 13 September 2024 -- Lucca -- 203212
URI: https://doi.org/10.1109/SPAWC60668.2024.10694490
https://hdl.handle.net/20.500.11851/11866
ISBN: 979-835039318-7
ISSN: 2325-3789
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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