Gaussian Process Regression for WDM System Performance Prediction

Jesper Wass; Jakob Thrane; Molly Piels; Rasmus Thomas Jones; Darko Zibar

doi:10.1364/OFC.2017.Tu3D.7

Gaussian Process Regression for WDM System Performance Prediction

Jesper Wass, Jakob Thrane, Molly Piels, Rasmus Thomas Jones, Darko Zibar

Centre of Excellence for Silicon Photonics for Optical Communications

MLytico

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

Abstract

Gaussian process regression is numerically and experimentally investigated to predict the bit error rate of a 24 x 28 CiBd QPSK WDM system. The proposed method produces accurate predictions from multi-dimensional and sparse measurement data.

Original language	English
Title of host publication	Optical Fiber Communication Conference 2017
Number of pages	3
Publisher	Optical Society of America (OSA)
Publication date	2017
Article number	Tu3D.7
ISBN (Print)	978-1-943580-23-1
DOIs	https://doi.org/10.1364/OFC.2017.Tu3D.7
Publication status	Published - 2017
Event	Optical Fiber Communication Conference 2017 - Los Angeles, United States Duration: 19 Mar 2017 → 23 Mar 2017

Conference

Conference	Optical Fiber Communication Conference 2017
Country/Territory	United States
City	Los Angeles
Period	19/03/2017 → 23/03/2017

Bibliographical note

From the session: Linear and Nonlinear Multicarrier Systems (Tu3D)

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10.1364/OFC.2017.Tu3D.7

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@inproceedings{08697cb587b84751816023506918ea61,

title = "Gaussian Process Regression for WDM System Performance Prediction",

abstract = "Gaussian process regression is numerically and experimentally investigated to predict the bit error rate of a 24 x 28 CiBd QPSK WDM system. The proposed method produces accurate predictions from multi-dimensional and sparse measurement data.",

author = "Jesper Wass and Jakob Thrane and Molly Piels and Jones, {Rasmus Thomas} and Darko Zibar",

note = "From the session: Linear and Nonlinear Multicarrier Systems (Tu3D); Optical Fiber Communication Conference 2017 ; Conference date: 19-03-2017 Through 23-03-2017",

year = "2017",

doi = "10.1364/OFC.2017.Tu3D.7",

language = "English",

isbn = "978-1-943580-23-1",

booktitle = "Optical Fiber Communication Conference 2017",

publisher = "Optical Society of America (OSA)",

}

TY - GEN

T1 - Gaussian Process Regression for WDM System Performance Prediction

AU - Wass, Jesper

AU - Thrane, Jakob

AU - Piels, Molly

AU - Jones, Rasmus Thomas

AU - Zibar, Darko

N1 - From the session: Linear and Nonlinear Multicarrier Systems (Tu3D)

PY - 2017

Y1 - 2017

N2 - Gaussian process regression is numerically and experimentally investigated to predict the bit error rate of a 24 x 28 CiBd QPSK WDM system. The proposed method produces accurate predictions from multi-dimensional and sparse measurement data.

AB - Gaussian process regression is numerically and experimentally investigated to predict the bit error rate of a 24 x 28 CiBd QPSK WDM system. The proposed method produces accurate predictions from multi-dimensional and sparse measurement data.

U2 - 10.1364/OFC.2017.Tu3D.7

DO - 10.1364/OFC.2017.Tu3D.7

M3 - Article in proceedings

SN - 978-1-943580-23-1

BT - Optical Fiber Communication Conference 2017

PB - Optical Society of America (OSA)

T2 - Optical Fiber Communication Conference 2017

Y2 - 19 March 2017 through 23 March 2017

ER -

Gaussian Process Regression for WDM System Performance Prediction

Abstract

Conference

Bibliographical note

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