A Kronecker-based sparse compressive sensing matrix for millimeter wave beam alignment

Erfan Khordad; Iain B. Collings; Stephen V. Hanly

doi:10.1109/ICSPCS47537.2019.9008733

A Kronecker-based sparse compressive sensing matrix for millimeter wave beam alignment

Erfan Khordad, Iain B. Collings, Stephen V. Hanly

School of Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

6 Citations (Scopus)

Abstract

Millimeter wave beam alignment (BA) is a challenging problem especially for large number of antennas. Compressed sensing (CS) tools have been exploited due to the sparse nature of such channels. This paper presents a novel deterministic CS approach for BA. Our proposed sensing matrix which has a Kronecker-based structure is sparse, which means it is computationally efficient. We show that our proposed sensing matrix satisfies the restricted isometry property (RIP) condition, which guarantees the reconstruction of the sparse vector. Our approach outperforms existing random beamforming techniques in practical low signal to noise ratio (SNR) scenarios.

Original language	English
Title of host publication	2019, 13th International Conference on Signal Processing and Communication Systems (ICSPCS)
Subtitle of host publication	proceedings
Editors	Tadeusz A. Wysocki, Beata J. Wysocki
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Number of pages	5
ISBN (Electronic)	9781728121949, 9781728121932
ISBN (Print)	9781728121956
DOIs	https://doi.org/10.1109/ICSPCS47537.2019.9008733
Publication status	Published - 2019
Event	13th International Conference on Signal Processing and Communication Systems, ICSPCS 2019 - Gold Coast, Australia Duration: 16 Dec 2019 → 18 Dec 2019

Conference

Conference	13th International Conference on Signal Processing and Communication Systems, ICSPCS 2019
Country/Territory	Australia
City	Gold Coast
Period	16/12/19 → 18/12/19

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10.1109/ICSPCS47537.2019.9008733

Cite this

Khordad, E., Collings, I. B., & Hanly, S. V. (2019). A Kronecker-based sparse compressive sensing matrix for millimeter wave beam alignment. In T. A. Wysocki, & B. J. Wysocki (Eds.), 2019, 13th International Conference on Signal Processing and Communication Systems (ICSPCS): proceedings Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICSPCS47537.2019.9008733

Khordad, Erfan ; Collings, Iain B. ; Hanly, Stephen V. / A Kronecker-based sparse compressive sensing matrix for millimeter wave beam alignment. 2019, 13th International Conference on Signal Processing and Communication Systems (ICSPCS): proceedings. editor / Tadeusz A. Wysocki ; Beata J. Wysocki. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2019.

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title = "A Kronecker-based sparse compressive sensing matrix for millimeter wave beam alignment",

abstract = "Millimeter wave beam alignment (BA) is a challenging problem especially for large number of antennas. Compressed sensing (CS) tools have been exploited due to the sparse nature of such channels. This paper presents a novel deterministic CS approach for BA. Our proposed sensing matrix which has a Kronecker-based structure is sparse, which means it is computationally efficient. We show that our proposed sensing matrix satisfies the restricted isometry property (RIP) condition, which guarantees the reconstruction of the sparse vector. Our approach outperforms existing random beamforming techniques in practical low signal to noise ratio (SNR) scenarios.",

author = "Erfan Khordad and Collings, {Iain B.} and Hanly, {Stephen V.}",

year = "2019",

doi = "10.1109/ICSPCS47537.2019.9008733",

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booktitle = "2019, 13th International Conference on Signal Processing and Communication Systems (ICSPCS)",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "13th International Conference on Signal Processing and Communication Systems, ICSPCS 2019 ; Conference date: 16-12-2019 Through 18-12-2019",

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Khordad, E, Collings, IB & Hanly, SV 2019, A Kronecker-based sparse compressive sensing matrix for millimeter wave beam alignment. in TA Wysocki & BJ Wysocki (eds), 2019, 13th International Conference on Signal Processing and Communication Systems (ICSPCS): proceedings. Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, 13th International Conference on Signal Processing and Communication Systems, ICSPCS 2019, Gold Coast, Australia, 16/12/19. https://doi.org/10.1109/ICSPCS47537.2019.9008733

A Kronecker-based sparse compressive sensing matrix for millimeter wave beam alignment. / Khordad, Erfan; Collings, Iain B.; Hanly, Stephen V.
2019, 13th International Conference on Signal Processing and Communication Systems (ICSPCS): proceedings. ed. / Tadeusz A. Wysocki; Beata J. Wysocki. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2019.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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T1 - A Kronecker-based sparse compressive sensing matrix for millimeter wave beam alignment

AU - Khordad, Erfan

AU - Collings, Iain B.

AU - Hanly, Stephen V.

PY - 2019

Y1 - 2019

N2 - Millimeter wave beam alignment (BA) is a challenging problem especially for large number of antennas. Compressed sensing (CS) tools have been exploited due to the sparse nature of such channels. This paper presents a novel deterministic CS approach for BA. Our proposed sensing matrix which has a Kronecker-based structure is sparse, which means it is computationally efficient. We show that our proposed sensing matrix satisfies the restricted isometry property (RIP) condition, which guarantees the reconstruction of the sparse vector. Our approach outperforms existing random beamforming techniques in practical low signal to noise ratio (SNR) scenarios.

AB - Millimeter wave beam alignment (BA) is a challenging problem especially for large number of antennas. Compressed sensing (CS) tools have been exploited due to the sparse nature of such channels. This paper presents a novel deterministic CS approach for BA. Our proposed sensing matrix which has a Kronecker-based structure is sparse, which means it is computationally efficient. We show that our proposed sensing matrix satisfies the restricted isometry property (RIP) condition, which guarantees the reconstruction of the sparse vector. Our approach outperforms existing random beamforming techniques in practical low signal to noise ratio (SNR) scenarios.

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DO - 10.1109/ICSPCS47537.2019.9008733

M3 - Conference proceeding contribution

SN - 9781728121956

BT - 2019, 13th International Conference on Signal Processing and Communication Systems (ICSPCS)

A2 - Wysocki, Tadeusz A.

A2 - Wysocki, Beata J.

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

T2 - 13th International Conference on Signal Processing and Communication Systems, ICSPCS 2019

Y2 - 16 December 2019 through 18 December 2019

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Khordad E, Collings IB , Hanly SV. A Kronecker-based sparse compressive sensing matrix for millimeter wave beam alignment. In Wysocki TA, Wysocki BJ, editors, 2019, 13th International Conference on Signal Processing and Communication Systems (ICSPCS): proceedings. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). 2019 doi: 10.1109/ICSPCS47537.2019.9008733

A Kronecker-based sparse compressive sensing matrix for millimeter wave beam alignment

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