<p> In this thesis we develop several approaches to the problem of blind channel equalization
based on second-order statistics (808). We consider the single-input singleoutput
(8180) system with minimum phase channel where the received signal is
sampled at the symbol rate (T-spaced equalizer). We formulate the equalizer design
criterion as a simple convex optimization problem, where the equalizer can be obtained
efficiently avoiding the local minima problem. </p> <p> We also extend the problem to the single-input multiple-output (8IMO) systems
where the received signal is sampled at an integer multiple of the symbol rate. We
formulate the problem as a convex optimization problem using the features existing
in the channel matrix structure. The problem can be solved efficiently to obtain the
equalizer where a global minima is guaranteed. Moreover, we modify this formulation
and deduce a closed form solution to the equalizer. Although both methods are sensitive
to the channel order as well as existing subspace methods, they perform better
than the subspace methods when the channel matrix is close to being singular.
Furthermore, we propose an efficient direct minimum mean square error (MM8E)
approach to estimate the equalizer. The method does not rely on the channel order
and utilizes the channel matrix structure in SIMO systems. Therefore, it outperforms
existing algorithms including the previously proposed methods. However, due
to the large amount of computations involved in this method we present a new algorithm
that belongs to the same class with moderate computational complexity and
acceptable performance loss with respect to the latter algorithm. </p> / Thesis / Master of Applied Science (MASc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/21870 |
| Date | 01 1900 |
| Creators | Farid, Ahmed |
| Contributors | Luo, Zhi-Quan (Tom), Electrical and Computer Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
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