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Open EDFA gain spectrum dataset and its applications in data-driven EDFA gain modeling

Publication ,  Journal Article
Wang, Z; Kilper, DC; Chen, T
Published in: Journal of Optical Communications and Networking
September 1, 2023

Optical networks satisfy high bandwidth and low latency requirements for telecommunication networks and data center interconnection. To improve network resource utilization, machine learning (ML) is used to accurately model optical amplifiers such as erbium-doped fiber amplifiers (EDFAs), which impact end-to-end system performance such as quality of transmission. However, a comprehensive measurement dataset is required for ML to accurately predict an EDFA's wavelength-dependent gain. We present an open dataset consisting of 202,752 gain spectrum measurements collected from 16 commercial-grade reconfigurable optical add-drop multiplexer (ROADM) booster and pre-amplifier EDFAs under varying gain settings and diverse channel-loading configurations over 2,785 hours in total, with a total dataset size of 3.1 GB. With this EDFA dataset, we implemented component-level deep-neural-network-based EDFA models and use transfer learning (TL) to transfer the EDFA model among 16 ROADM EDFAs, which achieve less than 0.18/0.24 dB mean absolute error for booster/pre-amplifier gain prediction using only 0.5% of the full target training set. We also showed that TL reduces the EDFA data collection requirements on a new gain setting or a different type of EDFA on the same ROADM.

Duke Scholars

Published In

Journal of Optical Communications and Networking

DOI

EISSN

1943-0639

ISSN

1943-0620

Publication Date

September 1, 2023

Volume

15

Issue

9

Start / End Page

588 / 599

Related Subject Headings

  • 4009 Electronics, sensors and digital hardware
  • 4006 Communications engineering
 

Citation

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MLA
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Wang, Z., Kilper, D. C., & Chen, T. (2023). Open EDFA gain spectrum dataset and its applications in data-driven EDFA gain modeling. Journal of Optical Communications and Networking, 15(9), 588–599. https://doi.org/10.1364/JOCN.491901
Wang, Z., D. C. Kilper, and T. Chen. “Open EDFA gain spectrum dataset and its applications in data-driven EDFA gain modeling.” Journal of Optical Communications and Networking 15, no. 9 (September 1, 2023): 588–99. https://doi.org/10.1364/JOCN.491901.
Wang Z, Kilper DC, Chen T. Open EDFA gain spectrum dataset and its applications in data-driven EDFA gain modeling. Journal of Optical Communications and Networking. 2023 Sep 1;15(9):588–99.
Wang, Z., et al. “Open EDFA gain spectrum dataset and its applications in data-driven EDFA gain modeling.” Journal of Optical Communications and Networking, vol. 15, no. 9, Sept. 2023, pp. 588–99. Scopus, doi:10.1364/JOCN.491901.
Wang Z, Kilper DC, Chen T. Open EDFA gain spectrum dataset and its applications in data-driven EDFA gain modeling. Journal of Optical Communications and Networking. 2023 Sep 1;15(9):588–599.
Journal cover image

Published In

Journal of Optical Communications and Networking

DOI

EISSN

1943-0639

ISSN

1943-0620

Publication Date

September 1, 2023

Volume

15

Issue

9

Start / End Page

588 / 599

Related Subject Headings

  • 4009 Electronics, sensors and digital hardware
  • 4006 Communications engineering