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Title:Equalization Using Graphical Models
Author(s):Drost, Robert James
Doctoral Committee Chair(s):Singer, Andrew C.
Department / Program:Electrical and Computer Engineering
Discipline:Electrical and Computer Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Engineering, Electronics and Electrical
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.
Issue Date:2007
Description:169 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.
Other Identifier(s):(MiAaPQ)AAI3290223
Date Available in IDEALS:2015-09-25
Date Deposited:2007

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