Low complexity carrier phase recovery based on Kalman filter with principal component analysis for coherent optical transmission system

In this paper, we propose a novel carrier phase recovery scheme based on Kalman filter with principal component analysis (KF-PCA) for coherent optical transmission system, which is a low-complexity, non-data-aided (NDA), feed-forward carrier phase recovery (CPR) algorithm. The proposed algorithm enables synchronous demodulation of square quadrature amplitude modulation (QAM) constellations and it is suitable for a practical hardware implementation based on block-wise parallel processing. The proposed algorithm is employed to obtain an optimal estimate of carrier phase with minimum mean squared error by data fusion of the predicted results and the observed results obtained from principal component analysis in the corresponding squared constellation. We demonstrate different transmission distances of 500-1500km and different optical signal-to-noise ratios (OSNR) values of a dual-polarization 40GBaud 16-QAM signal with root raised cosine (RRC) pulse shaping with a roll off factor of 0.02 by using the proposed algorithm in the offline digital signal processing (DSP). Numerical simulation results show that the proposed phase recovery algorithm outperforms the Kalman filter (KF) algorithm, showing much lower bit error rate (BER) both numerically and experimentally. And it achieves similar BER performance compared with the well-known and widely used blind phase search (BPS) algorithm. Additionally the complexity of the proposed methods represent an effective computational complexity reduction against BPS.