Multiparameter Monitoring of PAM4 Signals Using Deep Learning

Si Ao Li, Yuanpeng Liu, Yiwen Zhang, Wenqian Zhao, Tongying Shi, Xiao Han, Ivan B. Djordjevic, Yongxiong Ren, Changjing Bao, Zhongqi Pan, Yang Yue

Research output: Contribution to journalConference articlepeer-review

Abstract

PAM4 signal performance monitoring is demonstrated using CNN-based deep learning. A 98.51% prediction accuracy is achieved for jointly monitoring multiple parameters including baud rate, probabilistic shaping, roll-off factor, optical signal-to-noise ratio, and chromatic dispersion.

Original languageEnglish (US)
Article numberSW4E.3
JournalOptics InfoBase Conference Papers
StatePublished - 2022
EventCLEO: Science and Innovations, S and I 2022 - San Jose, United States
Duration: May 15 2022May 20 2022

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials

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