Robust Unambiguous Estimation of Angle-of-Arrival in Hybrid Array with Localized Analog Subarrays

Wu, K; Ni, W; Su, T; Liu, RP; Guo, YJ

Robust Unambiguous Estimation of Angle-of-Arrival in Hybrid Array with Localized Analog Subarrays

Wu, K

Ni, W

Su, T Liu, RP

Guo, YJ

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Wireless Communications, 2018, 17 (5), pp. 2987 - 3002
Issue Date:: 2018-05-01

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Field	Value	Language
dc.contributor.author	Wu, K https://orcid.org/0000-0003-1298-6404	en_US
dc.contributor.author	Ni, W https://orcid.org/0000-0002-4933-594X	en_US
dc.contributor.author	Su, T	en_US
dc.contributor.author	Liu, RP https://orcid.org/0000-0001-7001-6305	en_US
dc.contributor.author	Guo, YJ https://orcid.org/0000-0001-6008-9682	en_US
dc.date.issued	2018-05-01	en_US
dc.identifier.citation	IEEE Transactions on Wireless Communications, 2018, 17 (5), pp. 2987 - 3002	en_US
dc.identifier.issn	1536-1276	en_US
dc.identifier.uri	http://hdl.handle.net/10453/132638
dc.description.abstract	© 2018 IEEE. Hybrid array is able to leverage array gains, transceiver sizes, and costs for massive multiple-input-multiple-output systems in millimeter-wave frequencies. Challenges arise from the estimation of angle-of-arrival (AoA) in localized hybrid arrays, due to the array structure and the resultant estimation ambiguities and susceptibility to noises. This paper eliminates the ambiguities and enhances the tolerance to the noises based on our new discoveries. Particularly, by designing new subarray-specific time-varying phase shifts, we discover that the cross-correlations between the gains of consecutive subarrays have consistent signs except the strongest. This enables the cross-correlations to be deterministically calibrated and constructively combined for the noise-tolerant estimation of the propagation phase offset between adjacent subarrays. Given the phase offset, the AoA can be estimated unambiguously with few training symbols. We also derive a closed-form lower bound for the mean square error of AoA estimation. Corroborated by simulations, our approach is able to dramatically improve estimation accuracy by orders of magnitude while reducing complexity and training symbols, as compared to the state of the art. With the ambiguities eliminated, the estimation errors of our method asymptotically approach the lower bound, as training symbols increase.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP160102219
dc.relation.ispartof	IEEE Transactions on Wireless Communications	en_US
dc.relation.isbasedon	10.1109/TWC.2018.2805713	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Networking & Telecommunications	en_US
dc.title	Robust Unambiguous Estimation of Angle-of-Arrival in Hybrid Array with Localized Analog Subarrays	en_US
dc.type	Journal Article
utslib.citation.volume	5	en_US
utslib.citation.volume	17	en_US
utslib.for	1005 Communications Technologies	en_US
utslib.for	0805 Distributed Computing	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
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/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	closed_access	*
pubs.issue	5	en_US
pubs.publication-status	Published	en_US
pubs.volume	17	en_US

Abstract:

© 2018 IEEE. Hybrid array is able to leverage array gains, transceiver sizes, and costs for massive multiple-input-multiple-output systems in millimeter-wave frequencies. Challenges arise from the estimation of angle-of-arrival (AoA) in localized hybrid arrays, due to the array structure and the resultant estimation ambiguities and susceptibility to noises. This paper eliminates the ambiguities and enhances the tolerance to the noises based on our new discoveries. Particularly, by designing new subarray-specific time-varying phase shifts, we discover that the cross-correlations between the gains of consecutive subarrays have consistent signs except the strongest. This enables the cross-correlations to be deterministically calibrated and constructively combined for the noise-tolerant estimation of the propagation phase offset between adjacent subarrays. Given the phase offset, the AoA can be estimated unambiguously with few training symbols. We also derive a closed-form lower bound for the mean square error of AoA estimation. Corroborated by simulations, our approach is able to dramatically improve estimation accuracy by orders of magnitude while reducing complexity and training symbols, as compared to the state of the art. With the ambiguities eliminated, the estimation errors of our method asymptotically approach the lower bound, as training symbols increase.

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http://hdl.handle.net/10453/132638