Modeling and Tracking of Stochastic Polarization Drifts in Fiber-Optic Systems

Licentiate thesis, 2016

In the past decade, accessing information has become easier than ever, leading to a rapid growth in popularity of social media, online gaming, and multimedia broadcast systems. These and other services put pressure on the Internet service providers to support high-speed Internet connections and motivate the need for faster communication systems. Fiber-optic communications are the backbone of the Internet and accommodate for this demand by evolving from the traditional intensity-modulated systems to modern coherent detection, which makes use of digital signal processing to encode the data onto multiple phase and amplitude levels of the optical carrier. Although coherent systems enable the use of high-order modulation formats, the improved spectral efficiency comes at the cost of a reduced tolerance to impairments. These impairments are mitigated using digital signal processing algorithms, which, ideally, should be designed such that the impairments are optimally compensated in order to maximize performance. The impact of an impairment on the performance of a transmission system can be understood via a channel model, which should describe the behavior of the channel as accurately as possible. In this thesis, we consider modeling and compensation of the carrier phase noise and state of polarization drift in coherent fiber-optic systems. A theoretical framework is introduced to model the stochastic nature of the state of polarization during transmission. The model generalizes the one-dimensional carrier phase noise random walk to higher dimensions, modeling the phase noise and state of polarization drift jointly as rotations of the optical field and it has been successfully verified using experimental data. Such a model will be increasingly important in simulating and optimizing future systems, where sophisticated digital signal processing will be natural parts. The proposed polarization drift model is the first of its kind, as prior work either models polarization drift as a deterministic process or focuses on polarization-mode dispersion in systems where the state of polarization does not affect the receiver's performance. The typical digital signal processing solution to mitigate the phase noise and the drift of the state of polarization consists of two separate blocks that track each phenomenon independently. Such algorithms have been developed without taking into account mathematical models describing the impairments. Based on the proposed model, we study a blind tracking algorithm to compensate for these impairments. The algorithm dynamically recovers the carrier phase and state of polarization jointly for an arbitrary modulation format. Simulation results show the effectiveness of the proposed algorithm, having a fast convergence rate and an excellent tolerance to phase noise and dynamic drift of the polarization. The computational complexity of the algorithm is lower compared to state-of-the-art algorithms at similar or better performance, which makes it a strong candidate for future optical systems.