Estimating Network Components PDL Using Performance Statistical Measurements

In this paper, we propose a novel technique to estimate the polarization-dependent loss (PDL) of reconfigurable optical add-drop multiplexers (ROADMs) in a terrestrial optical network. The idea is to monitor the signal-to-noise ratio (SNR) distribution induced by the PDL and infer the corresponding PDL values through linear regression. The proposed method relies on only the mean and the variance of the SNR distribution, which can be collected by transceivers and sent to a central controller. The PDL regression algorithm and the methodology to acquire the statistical information are presented. We check the method accuracy for different link configurations. We show that our technique well predicts the ROADMs PDL obtaining an 80% uncertainty cut compared to the worst-case values provided by the datasheet for a ROADM after the transmitter and 40% for a ROADM in transit. We investigate two realistic light paths (LPs) of a network in the linear regime showing that the proposed PDL estimation reduces network SNR margins by more than 0.2 dB on these links. We also show that the nonlinear Kerr effect does not reduce the effectiveness of the method.