Flexible decision-aided maximum likelihood phase estimation in coherent optical phase-shift-keying systems

Abstract

Decision-aided maximum likelihood (DA-ML) phase estimation has been applied in coherent optical communication systems due to its high computational efficiency. However, conventional DA-ML scheme only assumes constant phase noise within each observation block, thus causing block length effect (BLE) which degrades system performance. In this paper, we take into account the time-varying laser phase noise and propose a flexible DA-ML phase estimation method for carrier phase recovery in coherent optical phase-shift-keying systems so as to eliminate BLE. Weighted coefficients based on ML criterion are introduced to strengthen the estimation accuracy. The statistical property of phase estimation error is derived, and the bit error rate (BER) performance is also evaluated. Numerical simulation results show that our flexible DA-ML scheme is very robust against time-varying phase noise. Compared with conventional DA-ML receiver, it can significantly reduce the phase estimation variance, improve the BER performance and increase the laser linewidth tolerance. By adopting the flexible DA-ML method with a relatively larger block length, BLE can be effectively eliminated. Thus, the BER performance can be significantly improved without carefully finding out the optimum block length or the optimum forgotten factor.