Unsupervised hierarchical clustering for blind nonlinear equalization in WDM coherent optical OFDM

Elias Giacoumidis*, Amir Matin, Jinlong Wei, Nick J. Doran, Xu Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We experimentally demonstrate the first Hierarchical clustering-based blind nonlinear equalizer for QPSK WDM-CO-OFDM. Hierarchical clustering outperforms to full-step digitalback propagation and artificial neural networks at 3200 km by up to 1.5 and 1.1 dB, respectively.

Original languageEnglish
Title of host publicationAsia Communications and Photonics Conference, ACPC 2017
PublisherOptical Society of America
VolumePart F83-ACPC 2017
ISBN (Electronic)9781557528209
DOIs
Publication statusPublished - 13 Nov 2017
EventAsia Communications and Photonics Conference, ACPC 2017 - Guangzhou, uangdong, China
Duration: 10 Nov 201713 Nov 2017

Conference

ConferenceAsia Communications and Photonics Conference, ACPC 2017
CountryChina
CityGuangzhou, uangdong
Period10/11/1713/11/17

Fingerprint

Quadrature phase shift keying
Equalizers
Carbon Monoxide
Wavelength division multiplexing
Orthogonal frequency division multiplexing
Neural networks

Cite this

Giacoumidis, E., Matin, A., Wei, J., Doran, N. J., & Wang, X. (2017). Unsupervised hierarchical clustering for blind nonlinear equalization in WDM coherent optical OFDM. In Asia Communications and Photonics Conference, ACPC 2017 (Vol. Part F83-ACPC 2017). Optical Society of America. https://doi.org/10.1364/ACPC.2017.Su4C.4
Giacoumidis, Elias ; Matin, Amir ; Wei, Jinlong ; Doran, Nick J. ; Wang, Xu. / Unsupervised hierarchical clustering for blind nonlinear equalization in WDM coherent optical OFDM. Asia Communications and Photonics Conference, ACPC 2017. Vol. Part F83-ACPC 2017 Optical Society of America, 2017.
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title = "Unsupervised hierarchical clustering for blind nonlinear equalization in WDM coherent optical OFDM",
abstract = "We experimentally demonstrate the first Hierarchical clustering-based blind nonlinear equalizer for QPSK WDM-CO-OFDM. Hierarchical clustering outperforms to full-step digitalback propagation and artificial neural networks at 3200 km by up to 1.5 and 1.1 dB, respectively.",
author = "Elias Giacoumidis and Amir Matin and Jinlong Wei and Doran, {Nick J.} and Xu Wang",
year = "2017",
month = "11",
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Giacoumidis, E, Matin, A, Wei, J, Doran, NJ & Wang, X 2017, Unsupervised hierarchical clustering for blind nonlinear equalization in WDM coherent optical OFDM. in Asia Communications and Photonics Conference, ACPC 2017. vol. Part F83-ACPC 2017, Optical Society of America, Asia Communications and Photonics Conference, ACPC 2017, Guangzhou, uangdong, China, 10/11/17. https://doi.org/10.1364/ACPC.2017.Su4C.4

Unsupervised hierarchical clustering for blind nonlinear equalization in WDM coherent optical OFDM. / Giacoumidis, Elias; Matin, Amir; Wei, Jinlong; Doran, Nick J.; Wang, Xu.

Asia Communications and Photonics Conference, ACPC 2017. Vol. Part F83-ACPC 2017 Optical Society of America, 2017.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Giacoumidis, Elias

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AU - Doran, Nick J.

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AB - We experimentally demonstrate the first Hierarchical clustering-based blind nonlinear equalizer for QPSK WDM-CO-OFDM. Hierarchical clustering outperforms to full-step digitalback propagation and artificial neural networks at 3200 km by up to 1.5 and 1.1 dB, respectively.

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Giacoumidis E, Matin A, Wei J, Doran NJ, Wang X. Unsupervised hierarchical clustering for blind nonlinear equalization in WDM coherent optical OFDM. In Asia Communications and Photonics Conference, ACPC 2017. Vol. Part F83-ACPC 2017. Optical Society of America. 2017 https://doi.org/10.1364/ACPC.2017.Su4C.4