Abstract
A low-cost OSNR monitoring method using artificial neural networks trained by frequency spectra of low-speed sampling signals is proposed. The monitoring range from 10.5 to 28.5 dB with error less than ± 0.5 dB is achieved.
© 2020 The Author(s)
PDF ArticleMore Like This
Yuanjian Li, Jing Zhang, Shaohua Hu, Wanting Zhang, Xingwen Yi, Zhenming Yu, Bo Xu, and Kun Qiu
C2F_5 Conference on Lasers and Electro-Optics/Pacific Rim (CLEO/PR) 2020
Feng Wang, Shencheng Ni, Shuying Han, Shanhong You, Ming Luo, and Zhixue He
M4A.246 Asia Communications and Photonics Conference (ACP) 2020
Ziyi Wang, Aiying Yang, Peng Guo, Lihui Feng, and Pinjing He
S4C.3 Asia Communications and Photonics Conference (ACP) 2018