An ML-Based Detector for Optical Communication in the Presence of Nonlinear Phase Noise

We present a closed-form maximum likelihood-based data detection algorithm for long-haul optical channels with dominant nonlinear phase noise induced by self-phase modulation. The closed-form detector is evaluated in terms of symbol error rate as a function of input power, and compared with other sub-optimal detectors as well as a non-parametric detector. We show that the performance of the detector deteriorates for high input power levels yielding an optimal operation region. We also provide insights into the behavior of the detector in the highly nonlinear regime.