Fast QoT estimation method using cascaded artificial neural network for real-time path provisioning in IMDD based all-optical networks-Reference-Cited by-同舟云学术

Fast QoT estimation method using cascaded artificial neural network for real-time path provisioning in IMDD based all-optical networks

Published:2024-01-02 Issue:2 Volume:32 Page:1176
ISSN:1094-4087
Container-title:Optics Express
language:en
Short-container-title:Opt. Express

Author:

Igarashi Ryo¹^ORCID,Koma Ryo¹,Hara Kazutaka¹,Kani Jun-ichi¹^ORCID,Yoshida Tomoaki¹

Affiliation:

1. NTT Access Network Service Systems Laboratories

Abstract

We propose a fast quality of transmission (QoT) estimation method based on cascaded artificial neural networks (ANNs) for intensity modulation-direct detection (IMDD) systems. The proposed method can calculate the bit error rate of three-span 36 km transmission within 0.7 seconds while taking account of the deterministic waveform distortion caused by the chromatic dispersion and self-phase modulation (SPM).

Publisher

Optica Publishing Group

Subject

Atomic and Molecular Physics, and Optics

Reference12 articles.

1. The OpenROADM initiative [Invited]

2. Photonic Gateway and Protocol-Independent End-to-End Optical-Connection Provisioning in All-Photonic Metro-Access Converged Network

3. Dynamic Optical Path Provisioning for Alien Access Links: Architecture, Demonstration, and Challenges

4. Machine-Learning-Based Lightpath QoT Estimation and Forecasting

5. Experimental Demonstration of Machine-Learning-Aided QoT Estimation in Multi-Domain Elastic Optical Networks with Alien Wavelengths

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