Convolutional Neural Network-Aided DP-64 QAM Coherent Optical Communication Systems-Reference-Cited by-同舟云学术

Convolutional Neural Network-Aided DP-64 QAM Coherent Optical Communication Systems

Published:2022-05-01 Issue:9 Volume:40 Page:2880-2889
ISSN:0733-8724
Container-title:Journal of Lightwave Technology
language:
Short-container-title:J. Lightwave Technol.

Author:

Li Chao¹^ORCID,Wang Yongjun¹^ORCID,Wang Jingjing²^ORCID,Yao Haipeng³^ORCID,Liu Xinyu⁴,Gao Ran⁴^ORCID,Yang Leijing¹,Xu Hui¹,Zhang Qi¹^ORCID,Ma Pengjie¹,Xin Xiangjun¹^ORCID

Affiliation:

1. School of Electronic Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing, China

2. School of Cyber Science and Technology, Beihang University, Beijing, China

3. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing, China

4. School of Information and Electronics, Beijing Institute of Technology, Zhongguancun South Street, Beijing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Young Elite Scientist Sponsorship Program by CAST

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atomic and Molecular Physics, and Optics

Link

http://xplorestaging.ieee.org/ielx7/50/9763567/09695357.pdf?arnumber=9695357

Reference29 articles.

1. Mixture-of-Gaussian clustering-based decision technique for a coherent optical communication system

2. Nonparameter Nonlinear Phase Noise Mitigation by Using M-ary Support Vector Machine for Coherent Optical Systems

3. Combatting nonlinear phase noise in coherent optical systems with an optimized decision processor based on machine learning;danshi;Opt Commun,2016

4. Comparison of DSP-based nonlinear equalizers for intra-channel nonlinearity compensation in coherent optical OFDM

5. Non-Data-Aided k-Nearest Neighbors Technique for Optical Fiber Nonlinearity Mitigation

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