A Simple Nonlinearity-Tailored Probabilistic Shaping Distribution for Square QAM

A new probabilistic shaping distribution that outperforms Maxwell-Boltzmann is studied for the nonlinear fiber channel. Additional gains of 0.1 bit/symbol MI or 0.2 dB SNR for both DP-256QAM and DP-1024QAM are reported after 200 km nonlinear fiber transmission

Deep Learning of Geometric Constellation Shaping including Fiber Nonlinearities

A new geometric shaping method is proposed, leveraging unsupervised machine learning to optimize the constellation design. The learned constellation mitigates nonlinear effects with gains up to 0.13 bit/4D when trained with a simplified fiber channel model.Comment: 3 pages, 6 figures, submitted to ECOC 201

Mitigation of inter-channel nonlinear interference in WDM systems

We demonstrate mitigation of inter-channel nonlinear interference noise (NLIN) in WDM systems for several amplification schemes. Using a practical decision directed recursive least-squares algorithm, we take advantage of the temporal correlations of NLIN to achieve a notable improvement in system performance

Joint Estimation of Linear and Non-linear Signal-to-Noise Ratio based on Neural Networks

A novel technique estimating ASE and non-linear SNR is presented. Our method is evaluated by simulations obtaining a std error of 0.23 dB for both ASE and non-linear SNR

High spectral efficiency transmission emulation for non-linear transmission performance estimation for high order modulation formats

We demonstrate a simple method to experimentally evaluate nonlinear transmission performance of high order modulation formats using a low number of channels and channel-like ASE. We verify it's behaviour is consistent with the AWGN model of transmission

Experimental Comparison of Probabilistic Shaping Methods for Unrepeated Fiber Transmission

\u3cp\u3eThis paper studies the impact of probabilistic shaping on effective signal-to-noise ratios (SNRs) and achievable information rates (AIRs) in a back-to-back configuration and in unrepeated nonlinear fiber transmissions. For the back-to-back setup, various shaped quadrature amplitude modulation (QAM) distributions are found to have the same implementation penalty as uniform input. By demonstrating in transmission experiments that shaped QAM input leads to lower effective SNR than uniform input at a fixed average launch power, we experimentally confirm that shaping enhances the fiber nonlinearities. However, shaping is ultimately found to increase the AIR, which is the most relevant figure of merit, as it is directly related to spectral efficiency. In a detailed study of these shaping gains for the nonlinear fiber channel, four strategies for optimizing QAM input distributions are evaluated and experimentally compared in wavelength division multiplexing (WDM) systems. The first shaping scheme generates a Maxwell-Boltzmann (MB) distribution based on a linear additive white Gaussian noise channel. The second strategy uses the Blahut-Arimoto algorithm to optimize an unconstrained QAM distribution for a split-step Fourier method based channel model. In the third and fourth approach, MB-shaped QAM and unconstrained QAM are optimized via the enhanced Gaussian noise (EGN) model. Although the absolute shaping gains are found to be relatively small, the relative improvements by EGN-optimized unconstrained distributions over linear AWGN optimized MB distributions are up to 59%. This general behavior is observed in 9-channel and fully loaded WDM experiments.\u3c/p\u3

Observing cross-channel NLI generation in disaggregated optical line systems

We investigate spatially separated XPM generation in a wide variety of 400G-ZR$+$ 64GBd pump-and-probe simulations, demonstrating the existence of a per-span upper bound that depends solely upon accumulated dispersion