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Spatial Correlation Modeling and RS-LS Estimation of Near-Field Channels with Uniform Planar Arrays
TOBB University of Economics and Technology, Department of Electrical-Electronics Engineering, Ankara, Türkiye.
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Communication Systems, CoS.ORCID iD: 0000-0001-7594-2367
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Communication Systems, CoS.ORCID iD: 0000-0002-5954-434X
2024 (English)In: 2024 IEEE 25th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2024, Institute of Electrical and Electronics Engineers (IEEE) , 2024, p. 236-240Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2024. p. 236-240
Keywords [en]
Extremely large-scale MIMO, near-field channels, reduced-subspace least-square estimator, spatial correlation
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:kth:diva-355493DOI: 10.1109/SPAWC60668.2024.10694490ISI: 001337964100048Scopus ID: 2-s2.0-85207062356OAI: oai:DiVA.org:kth-355493DiVA, id: diva2:1909481
Conference
25th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2024, Lucca, Italy, Sep 10 2024 - Sep 13 2024
Note

QC 20241031

Part of ISBN 9798350393187

Available from: 2024-10-30 Created: 2024-10-30 Last updated: 2025-01-20Bibliographically approved

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Kosasih, AlvaBjörnson, Emil

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