Abstract
A machine learning-based low-cost monitoring technique for transmitter IQ phase and gain imbalances is proposed. Simulations with formats up to NRZ-64QAM (28 GBd) show 95%-confidence estimation within 1.5° for phase and 0.06 for gain imbalances.
© 2018 The Author(s)
PDF ArticleMore Like This
Chao Gu, Qun Zhang, Yanfu Yang, and Yong Yao
C6F_2 Conference on Lasers and Electro-Optics/Pacific Rim (CLEO/PR) 2020
Md. Ibrahim Khalil, Arshad M Chowdhury, and Gee-Kung Chang
STu3J.1 CLEO: Science and Innovations (CLEO:S&I) 2014
Yuki Yoshida, Setsuo Yoshida, Shoichiro Oda, Takeshi Hoshida, and Naokatsu Yamamoto
Th5D.2 Optical Fiber Communication Conference (OFC) 2021