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.

A comparison between black-, gray- and white-box modeling for the bidirectional Raman amplifier optimization / Yankov, M.P., Soltani, M., Carena, A., Zibar, D., Da Ros, F.. - In: OPTICAL FIBER TECHNOLOGY. - ISSN 1068-5200. - ELETTRONICO. - 89:(2025). [10.1016/j.yofte.2024.104060]

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

Carena, Andrea;
2025

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3016858