Joint Modulation Format Identification and Optical Signal-to-Noise Ratio Monitoring Based on Ternary Neural Networks
Author:
Affiliation:
1. College of Computer Science & Information Engineering, Guangxi Normal University, Guilin, China
2. College of Electronic Engineering, Guangxi Normal University, Guilin, China
Funder
Guangxi S&T Program
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09992232.pdf?arnumber=9992232
Reference26 articles.
1. Modulation format identification in heterogeneous fiber-optic networks using artificial neural networks
2. Learning Constellation Map with Deep CNN for Accurate Modulation Recognition
3. Low-complexity and joint modulation format identification and OSNR estimation using random forest for flexible coherent receivers
4. A CNN-based cost-effective modulation format identification scheme by low-bandwidth direct detecting and low rate sampling for elastic optical networks
5. Modulation Scheme Identification Based on Artificial Neural Network Algorithms for Optical Communication System
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Research on Fault Location and Detection Technology of Optical Network Based on Long Short-Term Memory Neural Network;2023 IEEE 11th Joint International Information Technology and Artificial Intelligence Conference (ITAIC);2023-12-08
2. Optical Modulation Format Identification Under Hybrid OSNRs Using LIN Model;2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings (ACP/POEM);2023-11-04
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