Data-Driven Method for Nonlinear Optical Fiber Channel Modeling Based on Deep Neural Network

Recently, data-driven fiber channel modeling methods based on deep learning have been proposed in optical communication system simulations. We investigate a new data-driven method based on the deep neural network (DNN) to model the nonlinear fiber channel with the characteristics of attenuation, chr...

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Bibliographic Details
Published in:IEEE photonics journal 2022-08, Vol.14 (4), p.1-8
Main Authors: Jiang, Rui, Fu, Ziling, Bao, Yansheng, Wang, Huiying, Ding, Xin, Wang, Zhi
Format: Article
Language:English
Subjects:
and split-step fourier method
Artificial neural networks
Communications systems
Computer networks
Data-driven
deep learning
deep neural network
fiber channel modeling
Fiber nonlinear optics
fiber optics systems
Machine learning
Modelling
Modulation
Neural networks
Nonlinear optics
Optical attenuators
Optical communication
Optical fiber amplifiers
Optical fiber dispersion
Optical fiber networks
Optical fibers
Phase modulation
Spontaneous emission
Transfer functions
Waveforms
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Summary:Recently, data-driven fiber channel modeling methods based on deep learning have been proposed in optical communication system simulations. We investigate a new data-driven method based on the deep neural network (DNN) to model the nonlinear fiber channel with the characteristics of attenuation, chromatic dispersion, amplified spontaneous emission noise, self-phase modulation (SPM), and cross-phase modulation (XPM). Demonstration in multiple dimensions, including constellations, optical waveforms, spectra, and the normalized mean square error, shows that DNN can approach the transfer function of the fiber channel accurately. Additionally, the DNN shows good generalization for modulation formats and wavelength schemes. Besides, the time complexity of DNN-based method for modeling nonlinear fiber channel is reduced significantly (96.5%) compared to the conventional model-driven method, which is based on the split-step Fourier method. This work demonstrates that the DNN can model accurately the nonlinear fiber channel that takes account of both SPM and XPM. Therefore, it can contribute to the application of data-driven methods in modern optical communication system simulations and designs.
ISSN:1943-0655
1943-0655
1943-0647
DOI:10.1109/JPHOT.2022.3184354