Kerr Nonlinearity Dominance Diagnostic for Polarization-Dependent Loss Impaired Optical Transmissions

We present a method to classify optical transmission systems as linear or nonlinear based solely on signal-to-noise ratio statistics in presence of PDL-induced time-varying-performance. It obtains excellent accuracy (>95%), and it is proven accurate and robust under all the investigated conditions

Receiver-based fiber-optic link monitor

A digital processor (DP) is configured to obtain a temporal sequence of digital phase distortion measurements of a first optical signal received by a coherent optical receiver (COR) from an optical fiber link, where the first optical signal co-propagates with a second, power-modulated, optical signal in different frequency channels. The DP is configured to estimate a cross-correlation between the temporal sequence of digital measurements and a temporal sequence of powers of the second optical signal for a plurality of relative time shifts between the sequences, and to identify a location along the optical fiber link based on a magnitude of the cross-correlation exceeding a threshold for a particular time shift

Locating Fiber Loss Anomalies with a Receiver-side Monitoring Algorithm exploiting Cross-Phase Modulation

We propose and experimentally test a cross-phase modulation based algorithm to monitor network loss anomalies from detected data. The idea does not need service interruption, special signals, nor an exhaustive search of the anomaly coordinate

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

Multipoint Overlapping Optical Networks

Coherent transmission has drastically evolved in the last decade to provide high flexibility to improve spectral efficiency. This yields a point-to-point capacity close to Shannon's limit. In this work, we present the multipoint overlapping optical network architecture in a multi-transmitter to single-receiver context to boost the network capacity. It overlaps two optical signals, partly reusing network resources, here frequency slots of 12.5 GHz width. We show that a joint digital signal processing, based on multi-stage parallel interference cancellation efficiently compensates inter-channel interference up to 39% spectrum overlap with a 1 dB SNR penalty for PDM-QPSK signals. To investigate the impact of the residual interference penalty, we model the proposed solution as an additional power-independent Gaussian-noise term introduced in the transmission. Experiments and simulations have successfully validated the model and the extra penalty is shown to be dependent only on the chosen overlapping given factor. Finally, with such a model, we study the network gains brought by the proposed architecture. We investigate different networking scenarios assuming either 2-slot and 3-slot of overlapping, resulting in similar to 20% and similar to 40% of overlapping. We demonstrate a network capacity gain of up to 17%

Estimating Network Components Polarization-Dependent Loss Using Performance Statistical Measurements

We propose a novel approach to estimate reconfigurable optical add-drop multiplexers (ROADM) polarization-dependent loss (PDL) using the signal-to-noise ratio distribution induced by PDL. We show an uncertainty cut between 40% and 80% compared to datasheet in several configurations

The Gaussian Noise Model Extended to Polarization Dependent Loss and its Application to Outage Probability Estimation

We extend for the first time the Gaussian-noise model to account for polarization dependent loss (PDL) and validate it both numerically and experimentally. The model can be used to estimate outage probabilities induced by PDL-nonlinearity interaction in fast simulation times

Machine Learning-Driven Low-Complexity Optical Power Optimization for Point-to-Point Links

We propose a strategy to dynamically adjust transmitted power solely based on the analysis of performance fluctuations due to polarization-dependent loss. We show that our method converges faster to optimum compared to a standard approach