Optical performance monitoring via histogram: A data-driven approach

Yonggang Wen, Kevin W. Wilson
2009 2009 14th OptoElectronics and Communications Conference  
We apply three alternative statistical learning methods to estimate optical transmission impairments (e.g., noises, chromatic dispersion) from synchronous histograms. Linear regression yields good accuracy. A more sophisticated locally weighted regression technique performs better. OECC 2009 This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research
more » ... l and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Abstract 10Gbps RZ ASE Source Electrical Scope Fiber Variable Attenuator Optical Pre-Amp Optical Line-Amp PD Optical BPF Optical BPF Electrical BPF Fig. 1 Simulation setup: transmitter section, fiber link section and receiver section. We apply three alternative statistical learning methods to estimate optical transmission impairments (e.g., noises, chromatic dispersion) from synchronous histograms. Linear regression yields good accuracy. A more sophisticated locally weighted regression technique performs better.
doi:10.1109/oecc.2009.5222713 fatcat:qntogy5ukzb3topi7gu6pv4cvm