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https://hdl.handle.net/2142/81031
Description
Title
Equalization Using Graphical Models
Author(s)
Drost, Robert James
Issue Date
2007
Doctoral Committee Chair(s)
Singer, Andrew C.
Department of Study
Electrical and Computer Engineering
Discipline
Electrical and Computer Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Electronics and Electrical
Language
eng
Abstract
We examine the use of graphical models for the equalization of digital communication channels with memory. Graphical models provide a framework in which the structure of large systems can be exploited to derive efficient estimation algorithms. Furthermore, properties of a graph on which an algorithm is based can be used for analysis. We use factor graphs to develop efficient implementations of various equalization algorithms, including an unconstrained and a constrained linear minimum mean squared error equalizer and a generalized decision feedback equalizer. In addition to providing practical algorithms, the factor graph framework yields insight into their mechanics and interrelationships. We then consider algorithms for turbo equalization, using both graphical models and an algebraic approach to derive appropriate equalizers. In all cases, associated graphs are used for performance analysis. Finally, we consider universal piecewise linear equalization, adapting the well-known context-tree weighting algorithm. In addition, we generalize this approach by introducing context graphs that allow for a trade-off between modeling power and computational complexity. Although we focus primarily on equalization algorithms, many of the approaches considered are more general and can be applied to a wide variety of estimation problems.
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