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Flexible DA-ML Phase Estimation with Long Block Length
1  College of Communication and Information Engineering, Nanjing University of Posts and Telecommunications, CHINA


We review our previous efforts on exploring decision-aided maximum likelihood (DA-ML) phase estimation scheme for carrier phase recovery in coherent optical communication systems in view of its high linear computational efficiency. With the fundamental assumption of constant phase noise within each observation block, the block length effect (BLE) is expected to degrade system performance adversely. To counteract or even eliminate the effect, we recently proposed a flexible DA-ML phase estimation method by taking consideration of time-varying laser phase noise and weighted coefficients based on ML criterion. Numerical verifications show such a flexible DA-ML scheme is very robust against time-varying phase noise. It can reduce phase estimation variance and improve the laser linewidth tolerance, which result in BER performance improvement significantly. In practice, by adopting the flexible DA-ML method with a relatively longer block length, BLE can be completely eliminated. BER performance can thus be easily improved without careful search for optimum block length or forgotten factors.