Modeling and Compensation of Polarization Effects in Fiber-Optic Communication Systems
Doctoral thesis, 2018
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. 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 electric field and it has been successfully verified using experimental data. Thereafter, the model is extended to account for polarization-mode dispersion and its temporal random fluctuations. Such models will be increasingly important in simulating and optimizing future systems, where sophisticated digital signal processing will be natural parts.
The typical digital signal processing solution to mitigate phase noise and drift of the state of polarization consists of two separate blocks that track each phenomenon independently and have been developed without taking into account mathematical models describing the impairments. Based on the proposed model for the state of polarization, 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 and polarization noise.
The optical fiber is a nonlinear medium with respect to the intensity of the incident light. This effect leads to nonlinear interference as the intensity of light increases, which made nonlinear interference mitigation techniques to be an intensively studied topic. Typically, these techniques do not take into account polarization-mode dispersion, which becomes detrimental as the nonlinear effects interact with polarization-mode dispersion. We study digital-domain nonlinear interference mitigation algorithms that take into account polarization-mode dispersion by i) reversing the polarization effects concurrently with reversing the nonlinear effects and by ii) mitigating only the polarization-insensitive nonlinear contributions. These algorithms will be increasingly important in future optical systems capable of performing large bandwidth nonlinear interference mitigation, where even small amounts of polarization-mode dispersion become a limiting factor.
nonlinear compensation
Channel model
model-based
polarization demultiplexing
polarization-mode dispersion
polarization drift
backpropagation
PMD
DBP
Author
Cristian Bogdan Czegledi
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Polarization Drift Channel Model for Coherent Fibre-Optic Systems
Scientific Reports,;Vol. 6(2016)p. 21217-
Journal article
Temporal Stochastic Channel Model for Absolute Polarization State and Polarization-Mode Dispersion
2017 Optical Fiber Communications Conference and Exhibition (OFC),;(2017)p. Th3F.2 -
Paper in proceeding
Modulation Format Independent Joint Polarization and Phase Tracking for Coherent Receivers
Journal of Lightwave Technology,;Vol. 13(2016)p. 3354-3364
Journal article
Polarization-Mode Dispersion Aware Digital Backpropagation
42nd European Conference on Optical Communication, ECOC 2016; Dusseldorf; Germany; 18 September 2016 through 22 September 2016,;(2016)p. 1091-1093
Paper in proceeding
A PMD-adaptive DBP receiver based on SNR optimization
2018 OPTICAL FIBER COMMUNICATIONS CONFERENCE AND EXPOSITION (OFC),;(2018)
Paper in proceeding
Digital backpropagation accounting for polarization-mode dispersion
Optics Express,;Vol. 25(2017)p. 1903-1915
Journal article
Volterra Series Digital Backpropagation Accounting for PMD
European Conference on Optical Communication,;(2017)p. 1-3
Paper in proceeding
Subject Categories
Telecommunications
Communication Systems
Signal Processing
Infrastructure
C3SE (Chalmers Centre for Computational Science and Engineering)
ISBN
978-91-7597-702-7
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4383
Publisher
Chalmers
HC2
Opponent: Professor Mark Shtaif, Tel Aviv University, Israel