Tensor-Based Multi-Dimensional Wideband Channel Estimation for mmWave Hybrid Cylindrical Arrays

Lin, Z; Lv, T; Ni, W; Andrew Zhang, J; Liu, RP

Tensor-Based Multi-Dimensional Wideband Channel Estimation for mmWave Hybrid Cylindrical Arrays

Lin, Z

Lv, T Ni, W

Andrew Zhang, J Liu, RP

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Transactions on Communications, 2020, 68, (12), pp. 7608-7622
Issue Date:: 2020-12-01

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Field	Value	Language
dc.contributor.author	Lin, Z https://orcid.org/0000-0001-5941-2163
dc.contributor.author	Lv, T
dc.contributor.author	Ni, W https://orcid.org/0000-0002-4933-594X
dc.contributor.author	Andrew Zhang, J
dc.contributor.author	Liu, RP
dc.date.accessioned	2021-02-21T10:04:04Z
dc.date.available	2021-02-21T10:04:04Z
dc.date.issued	2020-12-01
dc.identifier.citation	IEEE Transactions on Communications, 2020, 68, (12), pp. 7608-7622
dc.identifier.issn	0090-6778
dc.identifier.issn	1558-0857
dc.identifier.uri	http://hdl.handle.net/10453/146251
dc.description.abstract	© 1972-2012 IEEE. Channel estimation is challenging for hybrid millimeter wave (mmWave) large-scale antenna arrays which are promising in 5G/B5G applications. The challenges are associated with angular resolution losses resulting from hybrid front-ends, beam squinting, and susceptibility to the receiver noises. Based on tensor signal processing, this paper presents a novel multi-dimensional approach to channel parameter estimation with large-scale mmWave hybrid uniform circular cylindrical arrays (UCyAs) which are compact in size and immune to mutual coupling but known to suffer from infinite-dimensional array responses and intractability. We design a new resolution-preserving hybrid beamformer and a low-complexity beam squinting suppression method, and reveal the existence of shift-invariance relations in the tensor models of received array signals at the UCyA. Exploiting these relations, we propose a new tensor-based subspace estimation algorithm to suppress the receiver noises in all dimensions (time, frequency, and space). The algorithm can accurately estimate the channel parameters from both coherent and incoherent signals. Corroborated by the Cramér-Rao lower bound (CRLB), simulation results show that the proposed algorithm is able to achieve substantially higher estimation accuracy than existing matrix-based techniques, with a comparable computational complexity.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation	CHINA ACADEMY OF TELECOMMUNICATION TECHNOLOGYCATT
dc.relation.ispartof	IEEE Transactions on Communications
dc.relation.isbasedon	10.1109/TCOMM.2020.3023934
dc.rights	© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.subject	0804 Data Format, 0906 Electrical and Electronic Engineering, 1005 Communications Technologies
dc.title	Tensor-Based Multi-Dimensional Wideband Channel Estimation for mmWave Hybrid Cylindrical Arrays
dc.type	Journal Article
utslib.citation.volume	68
utslib.for	0804 Data Format
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	1005 Communications Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	open_access	*
utslib.copyright.embargo	2022-12-31T00:00:00+1000Z
dc.date.updated	2021-02-21T10:03:54Z
pubs.issue	12
pubs.publication-status	Published
pubs.volume	68
utslib.citation.issue	12

Abstract:

© 1972-2012 IEEE. Channel estimation is challenging for hybrid millimeter wave (mmWave) large-scale antenna arrays which are promising in 5G/B5G applications. The challenges are associated with angular resolution losses resulting from hybrid front-ends, beam squinting, and susceptibility to the receiver noises. Based on tensor signal processing, this paper presents a novel multi-dimensional approach to channel parameter estimation with large-scale mmWave hybrid uniform circular cylindrical arrays (UCyAs) which are compact in size and immune to mutual coupling but known to suffer from infinite-dimensional array responses and intractability. We design a new resolution-preserving hybrid beamformer and a low-complexity beam squinting suppression method, and reveal the existence of shift-invariance relations in the tensor models of received array signals at the UCyA. Exploiting these relations, we propose a new tensor-based subspace estimation algorithm to suppress the receiver noises in all dimensions (time, frequency, and space). The algorithm can accurately estimate the channel parameters from both coherent and incoherent signals. Corroborated by the Cramér-Rao lower bound (CRLB), simulation results show that the proposed algorithm is able to achieve substantially higher estimation accuracy than existing matrix-based techniques, with a comparable computational complexity.

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