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, Özlem Tuğfe
Kosasih, Alva
Bjornson, Emil
Keywords: Extremely Large-Scale Mimo
Reduced-Subspace Least-Square Estimator
Spatial Correlation
Near-Field Channels
Publisher: Ieee
Series/Report no.: IEEE International Workshop on Signal Processing Advances in Wireless Communications
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 (RS-LS) 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.
URI: https://doi.org/10.1109/SPAWC60668.2024.10694490
ISBN: 9798350393194
9798350393187
ISSN: 1948-3244
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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