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Signal parameter estimation methods: The non-eigenvector based approach
Gami, Hirenkumar
Gami, Hirenkumar
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Dissertation
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2009-12
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Dissertation
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Electronic dissertations
Electronic dissertations
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Abstract
An idea behind this dissertation is the estimation of signal parameters of a radio channel
snapshot. The focal point here to utilize the high resolution estimation capabilities of subspace
based methods in association with non-eigenvector based parameter estimation methods to
reduce the complexity in wireless system parameter estimation process.
The first part of the work is to scrutinize various subspace based parametric estimation
methods in well explored array signal processing based wireless communication system problem.
These high resolution spectral parameter estimation methods broadly classified in terms of
eigenvector based and non-eigenvector based estimation methods. Although providing high
resolution and well-known in literature, the eigenvector based spectral parameter estimation
methods do not comply requirements of real time signal processing of today's highly complex
radio receivers. Therefore, this dissertation is focusing on computationally efficient noneigenvector
methods for signal spectral parameter estimation such as Rank Revealing QR
factorization, Propagator Method, Accelerated MUSIC, and other triangular factorization
methods.
The second part of this dissertation concentrate on performance evaluation of these noneigenvector
based methods in real world communication system problems. The performance of
these methods is demonstrated under three different parameter estimation problems such as
multipath time delay estimation in FH-CDMA system, channel estimation problem in MUMIMO
system, and joint parameter estimation problem in array signal processing. The role of
eigenvector based methods in the spectral parameter estimation is efficiently transformed into
non-eigenvector based parameter estimation procedure. This transformation leads to
development of computationally efficient algorithms with an enhanced estimation capability.
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Thesis (Ph.D.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science
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Wichita State University