The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 08, 2026

Filed:

Jan. 16, 2024
Applicant:

Nec Laboratories America, Inc., Princeton, NJ (US);

Inventors:

Fatih Yaman, Princeton, NJ (US);

Hussam Batshon, Monroe, NJ (US);

Eduardo Fabian Mateo Rodriguez, Tokyo, JP;

Yoshihisa Inada, Tokyo, JP;

Shinsuke Fujisawa, Tokyo, JP;

Takanori Inoue, Tokyo, JP;

Assignee:

NEC Corporation, Tokyo, JP;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H01S 3/10 (2006.01);
U.S. Cl.
CPC ...
H01S 3/10015 (2013.01); H01S 2301/04 (2013.01);
Abstract

Dependence of EDFA gain shape on input power and input spectrum shape is modelled using a simple neural network-based architecture for amplifiers with different gains and output powers. The model can predict the gain within ±0.1 dB. While the model has good success predicting the performance of an EDFA it is trained with, it is not as successful when predicting a different EDFA, or the same EDFA with different pump power. Retraining the model with a small amount of supplementary data from a separate EDFA makes the model able to predict the performance of the second EDFA with little loss in performance. Experiments show that machine learning model of an EDFA is capable of modelling spectralhole burning effects accurately. As a result, it significantly outperforms black-box models that neglect inhomogenous effects. Model achieves an average RMSE error of 0.016 dB between the model and measurements.


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