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Related papers: Multi-band programmable gain Raman amplifier

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Optical communication systems are always evolving to support the need for ever-increasing transmission rates. This demand is supported by the growth in complexity of communication systems which are moving towards ultra-wideband transmission…

A machine learning framework predicting pump powers and noise figure profile for a target distributed Raman amplifier gain profile is experimentally demonstrated. We employ a single-layer neural network to learn the mapping from the gain…

The throughput gains of extending the optical transmission bandwidth to the S+C+L-band are quantified using a Gaussian Noise model that accounts for inter-channel stimulated Raman scattering (ISRS). The impact of potential ISRS mitigation…

Signal Processing · Electrical Eng. & Systems 2020-06-17 Daniel Semrau , Eric Sillekens , Robert I. Killey , Polina Bayvel

A machine learning method for prediction of Raman gain and noise spectra is presented: it guarantees high-accuracy (RMSE < 0.4 dB) and low computational complexity making it suitable for real-time implementation in future optical networks…

Signal Processing · Electrical Eng. & Systems 2019-05-03 Ann Margareth Rosa Brusin , Vittorio Curri , Darko Zibar , Andrea Carena

All-optical signal processing is envisioned as an approach to dramatically decrease power consumption and speed up performance of next-generation optical telecommunications networks. Nonlinear optical effects, such as four-wave mixing (FWM)…

In this paper, ultra-broad band optical signal amplification are analyzed and demonstrated by utilizing supercontinuum generation propagating over the photonic crystal fiber. The coupled nonlinear Schroodinger equation containing parametric…

Optics · Physics 2018-11-02 Yikuan Li , Chun Jiang

Throughput optimization of optical communication systems is a key challenge for current optical networks. The use of gain-flattening filters (GFFs) simplifies the problem at the cost of insertion loss, higher power consumption and…

Machine Learning · Computer Science 2021-10-01 Metodi Plamenov Yankov , Pawel Marcin Kaminski , Henrik Enggaard Hansen , Francesco Da Ros

The ability to amplify optical signals is of pivotal importance across science and technology. The development of optical amplifiers has revolutionized optical communications, which are today pervasively used in virtually all sensing and…

The problem of Raman amplifier optimization is studied. A differentiable interpolation function is obtained for the Raman gain coefficient using machine learning (ML), which allows for the gradient descent optimization of…

Signal Processing · Electrical Eng. & Systems 2022-06-16 Metodi Plamenov Yankov , Francesco Da Ros , Uiara Celine de Moura , Andrea Carena , Darko Zibar

Modern optical communication systems transmit multiple frequency channels, each operating very close to its theoretical limit. The total bandwidth can reach 10THz limited by the optical amplifiers. Maximizing spectral efficiency, the…

Signal Processing · Electrical Eng. & Systems 2019-11-11 Mikael Mazur , Jochen Schröder , Magnus Karlsson , Peter A. Andrekson

A machine learning framework for Raman amplifier design is experimentally tested. Performance in terms of maximum error over the gain profile is investigated for various fiber types and lengths, demonstrating highly-accurate designs.

The potential benefits of extending the optical fibre transmission bandwidth are studied. Even in the presence of Kerr nonlinearity and inter-channel stimulated Raman scattering, increasing the usable optical fibre bandwidth appears to be…

Signal Processing · Electrical Eng. & Systems 2019-10-09 Gabriel Saavedra , Daniel Semrau , Polina Bayvel

We propose a n input parameter refinement scheme for the physics-based Raman amplifier model. Experiments over C+L band are conducted. Results show the scheme can lower the physical model's maximum estimation error by 2.13 dB.

Optics · Physics 2024-05-31 Yihao Zhang , Xiaomin Liu , Qizhi Qiu , Yichen Liu , Lilin Yi , Weisheng Hu , Qunbi Zhuge

Multi-band transmission is a promising technical direction for spectrum and capacity expansion of existing optical networks. Due to the increase in the number of usable wavelengths in multi-band optical networks, the complexity of resource…

Networking and Internet Architecture · Computer Science 2024-03-28 Cao Chen , Shilin Xiao , Fen Zhou , Massimo Tornatore

We experimentally validate a machine learning-enabled Raman amplification framework, capable of jointly shaping the signal power evolution in two domains: frequency and fiber distance. The proposed experiment addresses the amplification in…

Machine Learning · Computer Science 2022-06-16 Mehran Soltani , Francesco Da Ros , Andrea Carena , Darko Zibar

Cascades of a machine learning-based EDFA gain model trained on a single physical device and a fully differentiable stimulated Raman scattering fiber model are used to predict and optimize the power profile at the output of an experimental…

Signal Processing · Electrical Eng. & Systems 2020-09-14 Metodi P. Yankov , Uiara Celine de Moura , Francesco Da Ros

This paper presents an efficient numerical method for calculating spatial power profiles of both signal and pump with significant Interchannel Stimulated Raman Scattering (ISRS) and backward Raman amplification in multiband systems. This…

Signal Processing · Electrical Eng. & Systems 2025-04-09 Yanchao Jiang , Jad Sarkis , Stefano Piciaccia , Fabrizio Forghieri , Pierluigi Poggiolini

The effect of Kerr-induced optical fiber nonlinearities in C-band (5 THz) EDFA and C+L-band (12.5 THz) Raman-amplified optical communication systems has been studied considering the impact of third-order fiber dispersion. The performance of…

Signal Processing · Electrical Eng. & Systems 2019-09-25 Nikita A. Shevchenko , Tianhua Xu , Cenqin Jin , Domaniç Lavery , Robert I. Killey , Polina Bayvel

While ultrahigh-baud-rate optical signals are effective for extending the transmission distance of large capacity signals, they also reduce the number of wavelengths that can be arranged in a band because of their wider bandwidth. This…

A multi-layer neural network is employed to learn the mapping between Raman gain profile and pump powers and wavelengths. The learned model predicts with high-accuracy, low-latency and low-complexity the pumping setup for any gain profile.

Applied Physics · Physics 2018-11-27 D. Zibar , A. Ferrari , V. Curri , A. Carena
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