FRANÇAIS
A showcase of ÉTS researchers’ publications and other contributions
SEARCH

Classification of in-service optical time domain reflectometer trace changes using supervised learning

Tabatabaei, Mina, Pei, Yinqing, Boertjes, David, Desrosiers, Christian and Tremblay, Christine. 2024. « Classification of in-service optical time domain reflectometer trace changes using supervised learning ». In IEEE Future Networks World Forum (FNWF) (Dubai, UAE, Oct. 15-17, 2024) pp. 279-282. Institute of Electrical and Electronics Engineers Inc..
Compte des citations dans Scopus : 1.

[thumbnail of Tremblay-C-2024-30963.pdf]
Preview
PDF
Tremblay-C-2024-30963.pdf - Accepted Version
Use licence: All rights reserved to copyright holder.

Download (669kB) | Preview

Abstract

Optical fibers form the backbone of global telecommunications, and ensuring their reliability is crucial for network operators. Conventional Optical Time Domain Reflectometer (OTDR) methods focus on discrete events, but inservice measurements can detect distributed effects like fiber loss, Raman amplification, and Stimulated Raman Scattering (SRS) effects, which traditional methods struggle to handle. In this paper, we show how supervised learning models can effectively classify changes observed in in-service OTDR traces caused by fiber loss, Raman gain and channel loading. Multilayer Perceptron (MLP) outperformed Random Forest (RF) and Convolutional Neural Network (CNN) with 0.891 accuracy.

Item Type: Conference proceeding
Professor:
Professor
Desrosiers, Christian
Tremblay, Christine
Affiliation: Génie logiciel et des technologies de l'information, Génie électrique
Date Deposited: 22 May 2025 16:19
Last Modified: 08 Sep 2025 14:18
URI: https://espace2.etsmtl.ca/id/eprint/30963

Actions (login required)

View Item View Item