Data-Driven Method for Nonlinear Optical Fiber Channel Modeling Based on Deep Neural Network
Author:
Affiliation:
1. Institute of Optical Information, School of Science, Beijing Jiaotong University, Beijing, China
Funder
Beijing Natural Science Foundation
National Key R&D Plan
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics
Link
http://xplorestaging.ieee.org/ielx7/4563994/9795343/09800186.pdf?arnumber=9800186
Reference29 articles.
1. Nonlinear Impairment Compensation Using Neural Networks
2. Recurrent Neural Network Soft Demapping for Mitigation of Fiber Nonlinearities and ISI
3. Experimental Study of Deep Neural Network Equalizers Performance in Optical Links
4. Recurrent Neural Network based Equalizer with Embedded Parallelization for 100Gbps/λ PON
5. An Interpretable Mapping From a Communication System to a Neural Network for Optimal Transceiver-Joint Equalization
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