Fiber Nonlinear Compensation Using Bi-directional Recurrent Neural Network Model Based on Attention Mechanism-Reference-Cited by-同舟云学术

Fiber Nonlinear Compensation Using Bi-directional Recurrent Neural Network Model Based on Attention Mechanism

Published:2022-11-05 Issue: Volume: Page:
ISSN:
Container-title:2022 Asia Communications and Photonics Conference (ACP)
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Author:

Yang Xinzhi¹,Fang Zili¹,Zhang Wenbo¹,Xi Lixia²,Zhang Xiaoguang²,Cui Nan²

Affiliation:

1. Beijing University of Post and Telecommunications,State Key Laboratory of Information Photonics and Optical Communications, and School of Science,Beijing,China

2. Beijing University of Post and Telecommunications,State Key Laboratory of Information Photonics and Optical Communications,Beijing,China

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10088439/10088450/10088877.pdf?arnumber=10088877

Reference11 articles.

1. Nonlinear Interference Mitigation via Deep Neural Networks;hager;The Optical Fiber Communication Conference and Exposition (OFC),2018

2. Equalization performance and complexity analysis of dynamic deep neural networks in long haul transmission systems[J];oleg;Optics Express,2018

3. Neural Machine Translation by Jointly Learning to Align and Translate[J];bahdanau;Computer Science,2014

4. Mitigation of Nonlinearities in Optical Transmission Systems

5. Field and lab experimental demonstration of nonlinear impairment compensation using neural networks

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1. An Innovative Temporal Convolutional Network(TCN) Combined with Self-Attention Mechanism for Fiber Nonlinear Compensation;2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings (ACP/POEM);2023-11-04