Coherent Phase-Modulated Optical Fiber Communications with Linear and Nonlinear Phase Noise

Abstract

In this thesis, a computationally-linear decision aided (DA) maximum likelihood (ML) PE was introduced to eliminate the nonlinear computations while keeping or even improving the laser linewidth tolerance. We have conducted in-depth analysis on the performance of DA ML in different modulation formats, and observed that optimal memory length is related to the variances of the phase noise and additive noise. The parallel and serial implementations of the DA ML PE were also investigated to adapt itself to the high-speed optical receivers. However, the DA ML is subjected to the block length effect (BLE) because of a trade-off to average out the additive noise and phase noise. In order to address the BLE, a first-order filter was introduced to the DA ML algorithm, thus adaptively adjusting the filter gain based on the characteristics of the received signals. The adaptive DA algorithm was extended into the M-quadrature amplitude modulation (QAM) formats, where it was found that it suffers from the constellation penalty. Finally, two novel DSP algorithms were proposed to address the phase noises originating from the frequency offset and fiber nonlinearity, respectively.