Modulation format and baud-rate identification using asynchronous single channel sampling based on CNN

Jie Gao; Xian Zhou; Qirui Fan; Dongxu Lu; Jiahao Huo; Jinhui Yuan; Keping Long; Changyuan Yu; Alan Pak Tao Lau; Chao Lu

doi:10.1016/j.optcom.2020.125363

Modulation format and baud-rate identification using asynchronous single channel sampling based on CNN

Jie Gao, Xian Zhou, Qirui Fan, Dongxu Lu, Jiahao Huo, Jinhui Yuan, Keping Long, Changyuan Yu, Alan Pak Tao Lau, Chao Lu

The Hong Kong Polytechnic University

Research output: Journal article publication › Journal article › Academic research › peer-review

4 Citations (Scopus)

Abstract

In this paper, an asynchronous single channel sampling (ASCS) based joint modulation format and baud rate identification (MF–BRI) method is proposed for M-QAM optical systems using Convolutional Neural Network (CNN), which significantly reduces the cost and complexity of monitoring system setup. Based on the three influencing factors of OSNR, CD and DGD, three sampling rates are analyzed to generate ASCS images to build the database. The simulation and experiment accuracy of MFI and MF–BRI is above 99.8%. We also discuss the differences between two-channel sampling (TCS) and single-channel sampling (SCS).

Original language	English
Article number	125363
Journal	Optics Communications
Volume	463
DOIs	https://doi.org/10.1016/j.optcom.2020.125363
Publication status	Published - 15 May 2020

Keywords

Asynchronous single channel sampling
Convolutional Neural Network
Modulation format identification
Single channel sampling
Two channel sampling

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Atomic and Molecular Physics, and Optics
Physical and Theoretical Chemistry
Electrical and Electronic Engineering

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10.1016/j.optcom.2020.125363

Cite this

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title = "Modulation format and baud-rate identification using asynchronous single channel sampling based on CNN",

abstract = "In this paper, an asynchronous single channel sampling (ASCS) based joint modulation format and baud rate identification (MF–BRI) method is proposed for M-QAM optical systems using Convolutional Neural Network (CNN), which significantly reduces the cost and complexity of monitoring system setup. Based on the three influencing factors of OSNR, CD and DGD, three sampling rates are analyzed to generate ASCS images to build the database. The simulation and experiment accuracy of MFI and MF–BRI is above 99.8%. We also discuss the differences between two-channel sampling (TCS) and single-channel sampling (SCS).",

keywords = "Asynchronous single channel sampling, Convolutional Neural Network, Modulation format identification, Single channel sampling, Two channel sampling",

author = "Jie Gao and Xian Zhou and Qirui Fan and Dongxu Lu and Jiahao Huo and Jinhui Yuan and Keping Long and Changyuan Yu and Lau, {Alan Pak Tao} and Chao Lu",

year = "2020",

month = may,

day = "15",

doi = "10.1016/j.optcom.2020.125363",

language = "English",

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T1 - Modulation format and baud-rate identification using asynchronous single channel sampling based on CNN

AU - Gao, Jie

AU - Zhou, Xian

AU - Fan, Qirui

AU - Lu, Dongxu

AU - Huo, Jiahao

AU - Yuan, Jinhui

AU - Long, Keping

AU - Yu, Changyuan

AU - Lau, Alan Pak Tao

AU - Lu, Chao

PY - 2020/5/15

Y1 - 2020/5/15

N2 - In this paper, an asynchronous single channel sampling (ASCS) based joint modulation format and baud rate identification (MF–BRI) method is proposed for M-QAM optical systems using Convolutional Neural Network (CNN), which significantly reduces the cost and complexity of monitoring system setup. Based on the three influencing factors of OSNR, CD and DGD, three sampling rates are analyzed to generate ASCS images to build the database. The simulation and experiment accuracy of MFI and MF–BRI is above 99.8%. We also discuss the differences between two-channel sampling (TCS) and single-channel sampling (SCS).

AB - In this paper, an asynchronous single channel sampling (ASCS) based joint modulation format and baud rate identification (MF–BRI) method is proposed for M-QAM optical systems using Convolutional Neural Network (CNN), which significantly reduces the cost and complexity of monitoring system setup. Based on the three influencing factors of OSNR, CD and DGD, three sampling rates are analyzed to generate ASCS images to build the database. The simulation and experiment accuracy of MFI and MF–BRI is above 99.8%. We also discuss the differences between two-channel sampling (TCS) and single-channel sampling (SCS).

KW - Asynchronous single channel sampling

KW - Convolutional Neural Network

KW - Modulation format identification

KW - Single channel sampling

KW - Two channel sampling

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U2 - 10.1016/j.optcom.2020.125363

DO - 10.1016/j.optcom.2020.125363

M3 - Journal article

AN - SCOPUS:85078725270

SN - 0030-4018

VL - 463

JO - Optics Communications

JF - Optics Communications

M1 - 125363

ER -

Modulation format and baud-rate identification using asynchronous single channel sampling based on CNN

Abstract

Keywords

ASJC Scopus subject areas

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