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Performance Analysis of a 2D-MUSIC Algorithm for Parametric Near-Field Channel Estimation
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0001-5048-331X
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: 0000-0002-8822-6412
TOBB ETU, Dept Elect Elect Engn, TR-06560 Ankara, Turkiye.
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2025 (English)In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, Vol. 14, no 5, p. 1496-1500Article in journal (Refereed) Published
Abstract [en]

In this letter, we address parametric channel estimation in a multi-user multiple-input multiple-output system within the radiative near-field of the base station array with aperture antennas. We investigate a two-dimensional multiple signal classification algorithm (2D-MUSIC) to estimate both the range and the azimuth angles of arrival for the users' channels, utilizing parametric radiative near-field channel models. We analyze the performance of the algorithm by deriving the Cram & eacute;r-Rao bound (CRB) for parametric estimation, and its effectiveness is compared against the least squares estimator, which is a non-parametric estimator. Numerical results indicate that the 2D-MUSIC algorithm outperforms the least squares estimator. Furthermore, the results demonstrate that the performance of 2D-MUSIC achieves the parametric channel estimation CRB, which shows that the algorithm is asymptotically consistent.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2025. Vol. 14, no 5, p. 1496-1500
Keywords [en]
Channel estimation, Antennas, Vectors, Multiple signal classification, Aperture antennas, Parametric statistics, Lower bound, Covariance matrices, Azimuth, Approximation algorithms, Radiative near-field, MUSIC, Cram & eacute, r-Rao lower bound
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-364711DOI: 10.1109/LWC.2025.3547154ISI: 001484670400021Scopus ID: 2-s2.0-86000479329OAI: oai:DiVA.org:kth-364711DiVA, id: diva2:1980014
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QC 20250701

Available from: 2025-07-01 Created: 2025-07-01 Last updated: 2025-07-01Bibliographically approved

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Gurgunoglu, DogaKosasih, AlvaRamezani, ParisaBjörnson, EmilFodor, Gabor

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IEEE Wireless Communications Letters
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