Robust Carrier Phase Recovery in Probabilistically Shaped QAM via Adaptive EKF-ML

This article proposes an Extended Kalman Filtering (KF) with constellation-assisted maximum likelihood CPE technique to enhance carrier recovery performance in coherent optical communication systems employing probabilistic shaping (PS) by huge indicators. To assess how well EKF-ML, PCPE, and other state-of-the-art Kalman CPE methods work in B2B transmission scenarios over SFs of 0.02, 0.025, 0.03, and 0.035, we do numerical simulations. According to simulation data, EKF-ML outperforms other Kalman-based algorithms by an average of 0.5 to 1 dB and improves SNR by an average of 0.15 to 0.5 dB when compared to PCPE.