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Digital Equalization of Fiber-Optic Transmission System Impairments

<p>In the past half century, numerous improvements have been achieved to make fiber-optic communication systems overweigh other traditional transmission systems such as electrical coaxial systems in many applications. However, the physical features including fiber losses, chromatic dispersion, polarization mode dispersion, laser phase noise, and nonlinear effect still post a huge obstruction in fiber-optic communication system. In the past two decades, along with the evolution of digital signal processing system, digital approach to compensate these effects become a more simple and inexpensive solution.</p> <p>In this thesis, we discuss digital equalization techniques to mitigate the fiber-optic transmission impairments. We explain the methodology in our implementation of this simulation tool. Several major parts of such digital compensation scheme, such as laser phase noise estimator, fixed chromatic dispersion compensator, and adaptive equalizer, are discussed. Two different types of adaptive equalizer algorithm are also compared and discussed. Our results show that the digital compensation scheme using least mean square (LMS) algorithm can perfectly compensate all linear distortion effects, and laser phase noise compensator is optional in this scheme. Our result also shows that the digital compensation scheme using constant modulus algorithm (CMA) has about 3~4db power penalty compare to LMS algorithm. CMA algorithm has its advantage that it is capable of blind detection and self-recovery, but the laser phase noise compensator is not optional in this scheme. A digital compensation scheme which combines CMA and LMS algorithm would be a perfect receiver scheme for future work.</p> / Master of Applied Science (MASc)

Identiferoai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/11328
Date10 1900
CreatorsLuo, Ting
ContributorsKumar, Shiva, X. Li, W.P. Huang, X. Li, W.P. Huang, Electrical and Computer Engineering
Source SetsMcMaster University
Detected LanguageEnglish
Typethesis

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