Mitigating the Effects of Intersymbol Interference: Algorithms and Analysis
Nelson, Jill Karen
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/80935
Description
Title
Mitigating the Effects of Intersymbol Interference: Algorithms and Analysis
Author(s)
Nelson, Jill Karen
Issue Date
2005
Doctoral Committee Chair(s)
Andrew Singer
Department of Study
Electrical Engineering
Discipline
Electrical 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
In addition to asymptotic analysis of receivers for ISI channels, we also propose a joint maximum likelihood detection and decoding scheme for use when the channel is unknown to the receiver. Rather than employing training data to generate an estimate of the channel, the proposed receiver views the channel taps as stochastic quantities drawn from a known prior distribution and uses Bayesian techniques to compute estimates of the transmitted symbols. To implement the proposed receiver, we employ a stacklike algorithm, which estimates the transmitted bits by navigating the tree generated by the combined code and channel. We describe the derivation of the Bayesian metric and explore the performance loss incurred as a result of the lack of channel knowledge. In addition, we empirically characterize the robustness of the Bayesian detector to variations in the parameters of the prior distribution.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.