Joint Estimation of IQ Phase and Gain Imbalances Using Convolutional Neural Networks on Eye Diagrams

Stefano Savian; Júlio César Medeiros Diniz; Alan Pak Tao Lau; Faisal Nadeem Khan; Simone Gaiarin; Rasmus Thomas Jones; Darko Zibar

doi:10.1364/CLEO_SI.2018.STh1C.3

Joint Estimation of IQ Phase and Gain Imbalances Using Convolutional Neural Networks on Eye Diagrams

Stefano Savian
, Júlio César Medeiros Diniz
, Alan Pak Tao Lau
, Faisal Nadeem Khan
, Simone Gaiarin
, Rasmus Thomas Jones
, Darko Zibar

Centre of Excellence for Silicon Photonics for Optical Communications

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

Abstract

A machine learning-based low-cost monitoring technique for transmitter IQ phase and gain imbalances is proposed. Simulations with formats up to NRZ-64QAM (28 GBd) show 95%-confidence estimation within 1.5° for phase and 0.06 for gain imbalances.

Original language	English
Title of host publication	2018 Conference on Lasers and Electro-Optics (CLEO)
Number of pages	2
Publisher	Optical Society of America
Publication date	2018
Pages	1-2
ISBN (Print)	978-1-943580-42-2
DOIs	https://doi.org/10.1364/CLEO_SI.2018.STh1C.3
Publication status	Published - 2018
Event	CLEO: Science and Innovations 2018 - San Jose, United States Duration: 13 May 2018 → 18 May 2018 https://opg.optica.org/conference.cfm?meetingid=124&yr=2018

Conference

Conference	CLEO: Science and Innovations 2018
Country/Territory	United States
City	San Jose
Period	13/05/2018 → 18/05/2018
Internet address	https://opg.optica.org/conference.cfm?meetingid=124&yr=2018

Bibliographical note

From the session: Machine Learning for Communication (STh1C)

Keywords

Gain
Optical transmitters
Optical noise
Signal to noise ratio
Monitoring
Modulation
Adaptive optics

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10.1364/CLEO_SI.2018.STh1C.3

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@inproceedings{2a049ebdc11e4781916015fae3d078eb,

title = "Joint Estimation of IQ Phase and Gain Imbalances Using Convolutional Neural Networks on Eye Diagrams",

abstract = "A machine learning-based low-cost monitoring technique for transmitter IQ phase and gain imbalances is proposed. Simulations with formats up to NRZ-64QAM (28 GBd) show 95\%-confidence estimation within 1.5° for phase and 0.06 for gain imbalances.",

keywords = "Gain, Optical transmitters, Optical noise, Signal to noise ratio, Monitoring, Modulation, Adaptive optics",

author = "Stefano Savian and \{Medeiros Diniz\}, \{J{\'u}lio C{\'e}sar\} and Lau, \{Alan Pak Tao\} and Khan, \{Faisal Nadeem\} and Simone Gaiarin and Jones, \{Rasmus Thomas\} and Darko Zibar",

note = "From the session: Machine Learning for Communication (STh1C); CLEO: Science and Innovations 2018 ; Conference date: 13-05-2018 Through 18-05-2018",

year = "2018",

doi = "10.1364/CLEO\_SI.2018.STh1C.3",

language = "English",

isbn = "978-1-943580-42-2",

pages = "1--2",

booktitle = "2018 Conference on Lasers and Electro-Optics (CLEO)",

publisher = "Optical Society of America",

url = "https://opg.optica.org/conference.cfm?meetingid=124\&yr=2018",

}

Savian, S, Medeiros Diniz, JC, Lau, APT, Khan, FN, Gaiarin, S, Jones, RT & Zibar, D 2018, Joint Estimation of IQ Phase and Gain Imbalances Using Convolutional Neural Networks on Eye Diagrams. in 2018 Conference on Lasers and Electro-Optics (CLEO). Optical Society of America, pp. 1-2, CLEO: Science and Innovations 2018, San Jose, California, United States, 13/05/2018. https://doi.org/10.1364/CLEO_SI.2018.STh1C.3

Joint Estimation of IQ Phase and Gain Imbalances Using Convolutional Neural Networks on Eye Diagrams. / Savian, Stefano; Medeiros Diniz, Júlio César; Lau, Alan Pak Tao et al.
2018 Conference on Lasers and Electro-Optics (CLEO). Optical Society of America, 2018. p. 1-2.

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

TY - GEN

T1 - Joint Estimation of IQ Phase and Gain Imbalances Using Convolutional Neural Networks on Eye Diagrams

AU - Savian, Stefano

AU - Medeiros Diniz, Júlio César

AU - Lau, Alan Pak Tao

AU - Khan, Faisal Nadeem

AU - Gaiarin, Simone

AU - Jones, Rasmus Thomas

AU - Zibar, Darko

N1 - From the session: Machine Learning for Communication (STh1C)

PY - 2018

Y1 - 2018

N2 - A machine learning-based low-cost monitoring technique for transmitter IQ phase and gain imbalances is proposed. Simulations with formats up to NRZ-64QAM (28 GBd) show 95%-confidence estimation within 1.5° for phase and 0.06 for gain imbalances.

AB - A machine learning-based low-cost monitoring technique for transmitter IQ phase and gain imbalances is proposed. Simulations with formats up to NRZ-64QAM (28 GBd) show 95%-confidence estimation within 1.5° for phase and 0.06 for gain imbalances.

KW - Gain

KW - Optical transmitters

KW - Optical noise

KW - Signal to noise ratio

KW - Monitoring

KW - Modulation

KW - Adaptive optics

U2 - 10.1364/CLEO_SI.2018.STh1C.3

DO - 10.1364/CLEO_SI.2018.STh1C.3

M3 - Article in proceedings

SN - 978-1-943580-42-2

SP - 1

EP - 2

BT - 2018 Conference on Lasers and Electro-Optics (CLEO)

PB - Optical Society of America

T2 - CLEO: Science and Innovations 2018

Y2 - 13 May 2018 through 18 May 2018

ER -

Joint Estimation of IQ Phase and Gain Imbalances Using Convolutional Neural Networks on Eye Diagrams

Abstract

Conference

Bibliographical note

Keywords

Access to Document

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Cite this