Optical Performance Monitoring Via Histogram: A Data-Driven Approach
Source: Mitsubishi Electric
The authors 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. Optical Performance Monitoring (OPM) will be critical for reconfigurable all-optical networks in the future. Recent research has explored performance monitoring techniques that would reside on the optical layer of these future all-optical networks. In this paper, the authors focus their OPM work on quantitative assessment of two optical signal impairments, ASE noise level and fiber Chromatic Dispersion (CD).