GNPy: an open source application for physical layer aware open optical networks
In this paper, we describe the validation of GNPy. GNPy is an open source application that
approaches the optical layer according to a disaggregated paradigm, and its core engine is …
approaches the optical layer according to a disaggregated paradigm, and its core engine is …
Provisioning in multi-band optical networks
Multi-band (MB) optical transmission promises to extend the lifetime of existing optical fibre
infrastructures, which usually transmit within the C-band only, with C+ L-band being also …
infrastructures, which usually transmit within the C-band only, with C+ L-band being also …
Fast and accurate optical fiber channel modeling using generative adversarial network
H Yang, Z Niu, S Xiao, J Fang, Z Liu… - Journal of Lightwave …, 2020 - ieeexplore.ieee.org
In this work, a new data-driven fiber channel modeling method, generative adversarial
network (GAN) is investigated to learn the distribution of fiber channel transfer function. Our …
network (GAN) is investigated to learn the distribution of fiber channel transfer function. Our …
Analysis of nonlinear fiber interactions for finite-length constant-composition sequences
In order to realize probabilistically shaped signaling within the probabilistic amplitude
shaping (PAS) framework, a shaping device outputs sequences that follow a certain …
shaping (PAS) framework, a shaping device outputs sequences that follow a certain …
Modeling and mitigation of fiber nonlinearity in wideband optical signal transmission
The adoption of open optical networks (OONs) requires the development of open and
effective network planning tools, enabling the use of multi-vendor or white-box transport …
effective network planning tools, enabling the use of multi-vendor or white-box transport …
Novel suboptimal approaches for hyperparameter tuning of deep neural network [under the shelf of optical communication]
MA Amirabadi, MH Kahaei… - Physical Communication, 2020 - Elsevier
Grid search is the most effective method for tuning hyperparameters in machine learning
(ML). However, it has high computational complexity, and is not appropriate when here are …
(ML). However, it has high computational complexity, and is not appropriate when here are …
Accurate closed-form real-time EGN model formula leveraging machine-learning over 8500 thoroughly randomized full C-band systems
MR Zefreh, F Forghieri, S Piciaccia… - Journal of Lightwave …, 2020 - opg.optica.org
We derived an approximate non-linear interference (NLI) closed-form model (CFM), capable
of handling a very broad range of optical WDM system scenarios. We tested the CFM over …
of handling a very broad range of optical WDM system scenarios. We tested the CFM over …
The generalized droop formula for low signal to noise ratio optical links
We present a theoretical model that fully supports the recently disclosed generalized droop
formula (GDF) for calculating the signal-to-noise ratio (SNR) of constant-output power (COP) …
formula (GDF) for calculating the signal-to-noise ratio (SNR) of constant-output power (COP) …
Machine learning methods for optical communication systems and networks
Abstract Machine learning (ML) is being hailed as a new direction of innovation to transform
future optical communication systems. Signal processing paradigms based on ML are being …
future optical communication systems. Signal processing paradigms based on ML are being …
Fiber nonlinearity and optical system performance
This chapter aims to provide a comprehensive picture of the impact of fiber nonlinear effects
on modern coherent wavelength division multiplexing (WDM) systems' performance. First …
on modern coherent wavelength division multiplexing (WDM) systems' performance. First …