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 language | English (US) |
|---|---|
| Article number | SW4E.3 |
| Journal | Optics InfoBase Conference Papers |
| State | Published - 2022 |
| Event | CLEO: Science and Innovations, S and I 2022 - San Jose, United States Duration: May 15 2022 → May 20 2022 |
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Mechanics of Materials
Fingerprint
Dive into the research topics of 'Multiparameter Monitoring of PAM4 Signals Using Deep Learning'. Together they form a unique fingerprint.Cite this
- APA
- Standard
- Harvard
- Vancouver
- Author
- BIBTEX
- RIS