An Efficient Beam Training Technique for mmWave Communication Under NLoS Channel Conditions

Wenfang Yuan; Simon Armour; Angela Doufexi

doi:10.1109/WCNC.2016.7565091

An Efficient Beam Training Technique for mmWave Communication Under NLoS Channel Conditions

Wenfang Yuan, Simon Armour, Angela Doufexi

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

9 Citations (Scopus)

467 Downloads (Pure)

Abstract

An efficient codebook-based beam training technique is proposed for mmWave communication systems operating under non-line-of-sight (NLoS) channel conditions. Using convex optimization theory, this technique formulates the beam training process as a combinational optimization problem. It finds the best transmit-receive beam pair that maximizes the received signal power by iterating the Nelder-Mead simplex method through a multi-stage formulation of the training process. Compared with beamforming protocols adopted by 60 GHz WLAN/PAN systems, the proposed technique is robuster in NLoS scenarios. Simulation results demonstrate that the proposed technique achieves the same selection performance as the exhaustive search with a possibility of 87.6% while requiring moderate measurement steps.

Original language	English
Title of host publication	2016 IEEE Wireless Communications and Networking Conference (WCNC 2016)
Subtitle of host publication	Proceedings of a meeting held 3-6 April 2016, Doha, Qatar
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	2752-2757
Number of pages	6
ISBN (Print)	9781467398152
DOIs	https://doi.org/10.1109/WCNC.2016.7565091
Publication status	Published - Oct 2016

Publication series

Name	Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
ISSN (Print)	1558-2612

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10.1109/WCNC.2016.7565091

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SERAN: Seamless and Adaptive Wireless Access for Efficient Future Networks (SERAN)
Armour, S. M. D. (Principal Investigator)
1/01/15 → 31/12/18
Project: Research

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Yuan, W., Armour, S., & Doufexi, A. (2016). An Efficient Beam Training Technique for mmWave Communication Under NLoS Channel Conditions. In 2016 IEEE Wireless Communications and Networking Conference (WCNC 2016): Proceedings of a meeting held 3-6 April 2016, Doha, Qatar (pp. 2752-2757). (Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC)). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/WCNC.2016.7565091

Yuan, Wenfang ; Armour, Simon ; Doufexi, Angela. / An Efficient Beam Training Technique for mmWave Communication Under NLoS Channel Conditions. 2016 IEEE Wireless Communications and Networking Conference (WCNC 2016): Proceedings of a meeting held 3-6 April 2016, Doha, Qatar. Institute of Electrical and Electronics Engineers (IEEE), 2016. pp. 2752-2757 (Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC)).

@inproceedings{867525d30713497693090428d92671d6,

title = "An Efficient Beam Training Technique for mmWave Communication Under NLoS Channel Conditions",

abstract = "An efficient codebook-based beam training technique is proposed for mmWave communication systems operating under non-line-of-sight (NLoS) channel conditions. Using convex optimization theory, this technique formulates the beam training process as a combinational optimization problem. It finds the best transmit-receive beam pair that maximizes the received signal power by iterating the Nelder-Mead simplex method through a multi-stage formulation of the training process. Compared with beamforming protocols adopted by 60 GHz WLAN/PAN systems, the proposed technique is robuster in NLoS scenarios. Simulation results demonstrate that the proposed technique achieves the same selection performance as the exhaustive search with a possibility of 87.6% while requiring moderate measurement steps.",

author = "Wenfang Yuan and Simon Armour and Angela Doufexi",

year = "2016",

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doi = "10.1109/WCNC.2016.7565091",

language = "English",

isbn = "9781467398152",

series = "Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC)",

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

pages = "2752--2757",

booktitle = "2016 IEEE Wireless Communications and Networking Conference (WCNC 2016)",

address = "United States",

}

Yuan, W, Armour, S & Doufexi, A 2016, An Efficient Beam Training Technique for mmWave Communication Under NLoS Channel Conditions. in 2016 IEEE Wireless Communications and Networking Conference (WCNC 2016): Proceedings of a meeting held 3-6 April 2016, Doha, Qatar. Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC), Institute of Electrical and Electronics Engineers (IEEE), pp. 2752-2757. https://doi.org/10.1109/WCNC.2016.7565091

An Efficient Beam Training Technique for mmWave Communication Under NLoS Channel Conditions. / Yuan, Wenfang; Armour, Simon ; Doufexi, Angela.
2016 IEEE Wireless Communications and Networking Conference (WCNC 2016): Proceedings of a meeting held 3-6 April 2016, Doha, Qatar. Institute of Electrical and Electronics Engineers (IEEE), 2016. p. 2752-2757 (Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC)).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - An Efficient Beam Training Technique for mmWave Communication Under NLoS Channel Conditions

AU - Yuan, Wenfang

AU - Armour, Simon

AU - Doufexi, Angela

PY - 2016/10

Y1 - 2016/10

N2 - An efficient codebook-based beam training technique is proposed for mmWave communication systems operating under non-line-of-sight (NLoS) channel conditions. Using convex optimization theory, this technique formulates the beam training process as a combinational optimization problem. It finds the best transmit-receive beam pair that maximizes the received signal power by iterating the Nelder-Mead simplex method through a multi-stage formulation of the training process. Compared with beamforming protocols adopted by 60 GHz WLAN/PAN systems, the proposed technique is robuster in NLoS scenarios. Simulation results demonstrate that the proposed technique achieves the same selection performance as the exhaustive search with a possibility of 87.6% while requiring moderate measurement steps.

AB - An efficient codebook-based beam training technique is proposed for mmWave communication systems operating under non-line-of-sight (NLoS) channel conditions. Using convex optimization theory, this technique formulates the beam training process as a combinational optimization problem. It finds the best transmit-receive beam pair that maximizes the received signal power by iterating the Nelder-Mead simplex method through a multi-stage formulation of the training process. Compared with beamforming protocols adopted by 60 GHz WLAN/PAN systems, the proposed technique is robuster in NLoS scenarios. Simulation results demonstrate that the proposed technique achieves the same selection performance as the exhaustive search with a possibility of 87.6% while requiring moderate measurement steps.

U2 - 10.1109/WCNC.2016.7565091

DO - 10.1109/WCNC.2016.7565091

M3 - Conference Contribution (Conference Proceeding)

SN - 9781467398152

T3 - Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC)

SP - 2752

EP - 2757

BT - 2016 IEEE Wireless Communications and Networking Conference (WCNC 2016)

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -

Yuan W, Armour S , Doufexi A. An Efficient Beam Training Technique for mmWave Communication Under NLoS Channel Conditions. In 2016 IEEE Wireless Communications and Networking Conference (WCNC 2016): Proceedings of a meeting held 3-6 April 2016, Doha, Qatar. Institute of Electrical and Electronics Engineers (IEEE). 2016. p. 2752-2757. (Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC)). Epub 2016 Sept 15. doi: 10.1109/WCNC.2016.7565091

An Efficient Beam Training Technique for mmWave Communication Under NLoS Channel Conditions

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