Analytical Model of Nonlinear Fiber Propagation for General Dual-Polarization Four-Dimensional Modulation Format

TL;DR

This paper introduces a comprehensive analytical model for nonlinear fiber propagation in dual-polarization 4D modulation formats, accurately predicting nonlinear interference effects in long-haul optical systems.

Contribution

We develop a general analytical model that accounts for all NLI contributions in DP-4D formats, improving prediction accuracy over existing models.

Findings

Model predicts NLI with less than 0.15 dB gap from simulations.

Considering signal-noise interactions reduces transmission reach prediction error by 4%.

Model applies to all DP-4D modulation formats with independent symbols.

Abstract

Coherent dual-polarization (DP) optical transmission systems encode information on the four available degrees of freedom of an optical field: the two polarization states, each with two quadrature components. Such systems naturally operate based on a four-dimensional (4D) signal space. Having a general analytical model to accurately estimate nonlinear interference (NLI) is key to analyze such transmission systems as well as to study how different DP-4D formats are affected by NLI. However, the available models in the literature are not completely general. They either do not apply to the entire DP-4D formats or do not consider all the NLI contributions. In this paper, we develop a model that applies to all DP-4D modulation formats with independent symbols. Our model takes self-channel interference, cross-channel interference and multiple-channel interference effects into account. As an application of our model, we further study the effects of signal-noise interactions in long-haul transmission via the proposed model. When compared to previous results in the literature, our model is more accurate at predicting the contribution of NLI for both low and high dispersion fibers in single- and multi-channel transmission systems. For the NLI, we report an average gap from split step Fourier simulation results below 0.15 dB. The simulation results further show that by considering signal-noise interactions, the proposed model in long-haul transmission can reduce the transmission reach prediction error by 4%.