Abstract

We investigate the mitigation of nonlinearities with advanced digital signal processing focusing in particular on cross-polarization effects. Based on a relaxation of an analytical model derived for cross-polarization effects, this paper proposes a novel compensation method called generalized maximum likelihood. It performs a joint blind channel estimation and symbol detection, and it additionally accounts for the statistical prior distributions of the cross-polarization crosstalk coefficients. This avoids an overestimation of these crosstalk coefficients. A practical method for both fast computations and optimal performance is then presented, which allows nonlinear compensation for high-order modulations. Next, we present Monte–Carlo simulations showing that the proposed algorithm performs close to the theoretical limits. Large performance improvement can be obtained and this is particularly emphasized with higher order modulation such as a 16-ary quadrature amplitude modulation. Finally, using Nyquist pulse shaping and polarization-division multiplexed with a quadrature phase-shift keying modulation, the experiments are shown to be in accordance with the simulations and show up to 0.7 dB improvement in Q-factor for the worst-case samples.

© 2015 IEEE

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