Digital predistortion enhancement by convolutional neural network for probabilistic shaped discrete multi-tone signal transmission in passive optical network

Qi Zhou; Rui Zhang; Shuyi Shen; Chin Wei Hsu; Shuang Yao; Shang Jen Su; Gee Kung Chang

Digital predistortion enhancement by convolutional neural network for probabilistic shaped discrete multi-tone signal transmission in passive optical network

Qi Zhou
, Rui Zhang
, Shuyi Shen
, Chin Wei Hsu
, Shuang Yao
, Shang Jen Su
, Gee Kung Chang

Department of Electrical Engineering

University at Buffalo

Georgia Institute of Technology

Research output: Contribution to journal › Conference article › peer-review

Abstract

We experimentally demonstrate a 68.2-Gb/s net data-rate probabilistic shaped discrete multi-tone transmission in passive optical network with 11G-class devices. The convolutional-neural-network strengthens digital predistortion performance with 1.1-dB improvement of system sensitivity over linear pre-equalization.

Original language	English
Journal	Optics InfoBase Conference Papers
State	Published - 2021
Event	Optical Fiber Communication Conference, OFC 2021 - Virtual, Online, United States Duration: Jun 6 2021 → Jun 11 2021

Cite this

@article{f5016348caad4622aadd821a68d4f946,

title = "Digital predistortion enhancement by convolutional neural network for probabilistic shaped discrete multi-tone signal transmission in passive optical network",

abstract = "We experimentally demonstrate a 68.2-Gb/s net data-rate probabilistic shaped discrete multi-tone transmission in passive optical network with 11G-class devices. The convolutional-neural-network strengthens digital predistortion performance with 1.1-dB improvement of system sensitivity over linear pre-equalization.",

author = "Qi Zhou and Rui Zhang and Shuyi Shen and Hsu, \{Chin Wei\} and Shuang Yao and Su, \{Shang Jen\} and Chang, \{Gee Kung\}",

note = "Publisher Copyright: {\textcopyright} OSA 2021, {\textcopyright} 2021 The Author(s); Optical Fiber Communication Conference, OFC 2021 ; Conference date: 06-06-2021 Through 11-06-2021",

year = "2021",

language = "English",

journal = "Optics InfoBase Conference Papers",

issn = "2162-2701",

}

TY - JOUR

T1 - Digital predistortion enhancement by convolutional neural network for probabilistic shaped discrete multi-tone signal transmission in passive optical network

AU - Zhou, Qi

AU - Zhang, Rui

AU - Shen, Shuyi

AU - Hsu, Chin Wei

AU - Yao, Shuang

AU - Su, Shang Jen

AU - Chang, Gee Kung

PY - 2021

Y1 - 2021

N2 - We experimentally demonstrate a 68.2-Gb/s net data-rate probabilistic shaped discrete multi-tone transmission in passive optical network with 11G-class devices. The convolutional-neural-network strengthens digital predistortion performance with 1.1-dB improvement of system sensitivity over linear pre-equalization.

AB - We experimentally demonstrate a 68.2-Gb/s net data-rate probabilistic shaped discrete multi-tone transmission in passive optical network with 11G-class devices. The convolutional-neural-network strengthens digital predistortion performance with 1.1-dB improvement of system sensitivity over linear pre-equalization.

UR - https://www.scopus.com/pages/publications/85133788871

M3 - Conference article

SN - 2162-2701

JO - Optics InfoBase Conference Papers

JF - Optics InfoBase Conference Papers

T2 - Optical Fiber Communication Conference, OFC 2021

Y2 - 6 June 2021 through 11 June 2021

ER -

Digital predistortion enhancement by convolutional neural network for probabilistic shaped discrete multi-tone signal transmission in passive optical network

Abstract

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