A comparison between black-, gray- and white-box modeling for the bidirectional Raman amplifier optimization

Metodi P. Yankov, Mehran Soltani, Andrea Carena, Darko Zibar, Francesco Da Ros*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Designing and optimizing optical amplifiers to maximize system performance is becoming increasingly important as optical communication systems strive to increase throughput. Offline optimization of optical amplifiers relies on models ranging from white-box models deeply rooted in physics to black-box data-driven and physics-agnostic models. Here, we compare the capabilities of white-, gray- and black-box models on the challenging test case of optimizing a bidirectional distributed Raman amplifier to achieve a target frequency-distance signal power profile. We show that any of the studied methods can achieve similar frequency and distance flatness of between 1 and 3.6 dB (depending on the definition of flatness) over the C-band in an 80-km span. Then, we discuss the models’ applicability, advantages, and drawbacks based on the target application scenario, in particular in terms of flexibility, optimization speed, and access to training data.

Original languageEnglish
Article number104060
JournalOptical Fiber Technology
Volume89
Number of pages6
ISSN1068-5200
DOIs
Publication statusPublished - Jan 2025

Keywords

  • Machine learning
  • Modeling
  • Raman amplifiers

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