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Gridless Hybrid-Field Channel Estimation for Extra-Large Aperture Array Massive MIMO Systems
Xi, Yang1; Zhu, Fuqiang1; Zhou, Binggui3; Liu, Ting2; Ma, Shaodan3
2024-02-01
Source PublicationIEEE Wireless Communications Letters
ISSN2162-2337
Volume13Issue:2Pages:496-500
Abstract

Channel estimation is significant for extra-large aperture array (ELAA) massive multiple-input multiple-output (MIMO) systems to fully fulfill their potential. However, hybrid-field propagation environment appears due to adopting ELAA, which thereby severely degrades the performance of existing channel estimation algorithms designed based on the channel sparsity property in traditional beam/angle domains. To tackle this problem, we propose a gridless hybrid-field channel estimation algorithm in this letter by excavating the hybrid-field channel sparsity in the fractional Fourier domain. The hybrid-field channel estimation problem is first formulated, and then the discrete fractional Fourier transform (DFrFT) is introduced to reveal the channel sparsity in the fractional Fourier domain. After that, the DFrFT-based Newtonized orthogonal matching pursuit algorithm is proposed without prior knowledge of the number of propagation paths. Numerical results show that the proposed algorithm greatly outperforms the existing algorithms.

KeywordChannel Estimation Elaa Massive Mimo Fractional Fourier Transform Hybrid Field Normalized Mean-squared Error
DOI10.1109/LWC.2023.3333531
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science ; Engineering ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:001167560000050
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141
Scopus ID2-s2.0-85178032923
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Citation statistics
Document TypeJournal article
CollectionTHE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
Faculty of Science and Technology
DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
Corresponding AuthorXi, Yang; Zhou, Binggui
Affiliation1.East China Normal University, Shanghai Key Laboratory of Multidimensional Information Processing, School of Communication and Electronic Engineering, Shanghai, 200241, China
2.Nanjing University of Information Science and Technology, Institute of Artificial Intelligence, Nanjing, 210096, China
3.University of Macau, State Key Laboratory of Internet of Things for Smart City, The Department of Electrical and Computer Engineering, Macao
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Xi, Yang,Zhu, Fuqiang,Zhou, Binggui,et al. Gridless Hybrid-Field Channel Estimation for Extra-Large Aperture Array Massive MIMO Systems[J]. IEEE Wireless Communications Letters, 2024, 13(2), 496-500.
APA Xi, Yang., Zhu, Fuqiang., Zhou, Binggui., Liu, Ting., & Ma, Shaodan (2024). Gridless Hybrid-Field Channel Estimation for Extra-Large Aperture Array Massive MIMO Systems. IEEE Wireless Communications Letters, 13(2), 496-500.
MLA Xi, Yang,et al."Gridless Hybrid-Field Channel Estimation for Extra-Large Aperture Array Massive MIMO Systems".IEEE Wireless Communications Letters 13.2(2024):496-500.
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