Impact of 4D channel distribution on the achievable rates in coherent optical communication experiments
Tobias A. Eriksson, Tobias Fehenberger, Peter A. Andrekson, Magnus Karlsson, Norbert Hanik, Erik Agrell
TL;DR
This work experimentally evaluates how channel distribution assumptions affect achievable information rates in coherent optical communication. By comparing MI and GMI under 2D and 4D Gaussian models, with static and adaptive mean estimates, the study shows that 2D iid Gaussian noise is a solid default for many practical WDM links without inline dispersion compensation, while 4D correlated Gaussian models with adaptive means provide small but meaningful gains for links with inline dispersion compensation and nonlinear effects. The results highlight the trade off between decoder complexity and rate gains, suggesting modest improvements from 4D modeling in specific configurations while keeping simpler models adequate in others. Overall, the findings guide channel modeling choices for rate estimation and decoder design in modern fiber-optic systems, particularly under nonlinear and dispersion-managed conditions.
Abstract
We experimentally investigate mutual information and generalized mutual information for coherent optical transmission systems. The impact of the assumed channel distribution on the achievable rate is investigated for distributions in up to four dimensions. Single channel and wavelength division multiplexing (WDM) transmission over transmission links with and without inline dispersion compensation are studied. We show that for conventional WDM systems without inline dispersion compensation, a circularly symmetric complex Gaussian distribution is a good approximation of the channel. For other channels, such as with inline dispersion compensation, this is no longer true and gains in the achievable information rate are obtained by considering more sophisticated four-dimensional (4D) distributions. We also show that for nonlinear channels, gains in the achievable information rate can also be achieved by estimating the mean values of the received constellation in four dimensions. The highest gain for such channels is seen for a 4D correlated Gaussian distribution.