Optical network physical layer parameter optimization for digital backpropagation using Gaussian processes

We present a novel methodology for optimizing fiber optic network performance by determining the ideal values for attenuation, nonlinearity, and dispersion parameters in terms of achieved signal-to-noise ratio (SNR) gain from digital backpropagation (DBP). Our approach uses Gaussian process regression, a probabilistic machine learning technique, to create a computationally efficient model for mapping these parameters to the resulting SNR after applying DBP. We then use simplicial homology global optimization to find the parameter values that yield maximum SNR for the Gaussian process model within a set of a priori bounds. This approach optimizes the parameters in terms of the DBP gain at the receiver. We demonstrate the effectiveness of our method through simulation and experimental testing, achieving optimal estimates of the dispersion, nonlinearity, and attenuation parameters. Our approach also highlights the limitations of traditional one-at-a-time grid search methods and emphasizes the interpretability of the technique. This methodology has broad applications in engineering and can be used to optimize performance in various systems beyond optical networks

A Comparison of Impairment Abstractions by Multiple Users of an Installed Fiber Infrastructure

We compare three independent impairment abstractions of an installed fibre infrastructure. Abstractions agreed to within 1.3dB despite being obtained from different nodes using different terminal equipment. Validation using a DWDM virtual topology was within 1.4dB

Distributed abstraction and verification of an installed optical fibre network.

The management of wavelength routed optical mesh networks is complex with many potential light path routes and numerous physical layer impairments to transmission performance. This complexity can be reduced by applying the ideas of abstraction from computer science where different equipment is described in the same basic terms. The noise-to-signal ratio can be used as a metric to describe the quality of transmission performance of a signal propagated through a network element and accumulates additively through a sequence of such elements allowing the estimation of end-to-end performance. This study aims to explore the robustness of the noise-to-signal ratio metric in an installed fibre infrastructure. We show that the abstracted noise-to-signal ratio is independent of the observers and their location. We confirm that the abstracted noise-to-signal ratio can reasonably predict the performance of light-paths subsequently set in our network. Having a robust network element abstraction that can be incorporated into routeing engines allows the network management controller to make decisions on the most effective way to use the network resources in terms of the routeing and data coding format

Unrepeatered Transmission Over 253.4 km Ultra Low Loss Fibre Achieving 6.95 (b/s)/Hz Se Using EDFA-Only Pre-Amplifier

A 560 Gb/s (7×80 Gb/s Nyquist spaced PDM-16QAM) superchannel achieving 6.95 b/s/Hz spectral efficiency is transmitted over 253.4 km SMF-28® ULL fiber using only EDFA pre-amplification and full-field nonlinear back-propagation, corresponding to a record SE-distance product of 1761.1 b/s/Hz·km

Distributed abstraction and verification of an installed optical fibre network

Abstract: The management of wavelength routed optical mesh networks is complex with many potential light path routes and numerous physical layer impairments to transmission performance. This complexity can be reduced by applying the ideas of abstraction from computer science where different equipment is described in the same basic terms. The noise-to-signal ratio can be used as a metric to describe the quality of transmission performance of a signal propagated through a network element and accumulates additively through a sequence of such elements allowing the estimation of end-to-end performance. This study aims to explore the robustness of the noise-to-signal ratio metric in an installed fibre infrastructure. We show that the abstracted noise-to-signal ratio is independent of the observers and their location. We confirm that the abstracted noise-to-signal ratio can reasonably predict the performance of light-paths subsequently set in our network. Having a robust network element abstraction that can be incorporated into routeing engines allows the network management controller to make decisions on the most effective way to use the network resources in terms of the routeing and data coding format

Transport policy : journal of the World Conference on Transport Research Society

A RRC filter with a 0.1% roll-off factor reduces the impact of linear crosstalk-induced penalty in a Nyquist spaced 10GBd DP-16QAM transmission system with a net ISD of 7.47(b/s)/Hz and the maximum reach is extended to 1940km using full-field DBP

The Western historical quarterly

A 560 Gb/s (7×80 Gb/s Nyquist spaced PDM-16QAM) superchannel achieving 6.95 b/s/Hz spectral efficiency is transmitted over 253.4 km SMF-28® ULL fiber using only EDFA pre-amplification and full-field nonlinear back-propagation, corresponding to a record SE-distance product of 1761.1 b/s/Hz·km