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Blind Identification of MIMO Systems: Signal Modulation and Channel Estimation

Present trends in communication links between devices have opted for wireless instead of wired solutions. As a consequence, unlicensed bands have seen a rise in the interference level as more and more devices are introduced into the market place that take advantage of these free bands for their communication needs. Under these conditions, the receiver's ability to recognize and identify the presence of interference becomes increasingly important. In order for the receiver to make an optimal decision on the signal-of-interest, it has to be aware of the type (modulation) of interference as well as how the received signals are affected (channel) by these impediments in order to appropriately mitigate them.

This dissertation addresses the blind (unaided) identification of the signal modulations and the channel in a Multiple Input Multiple Output (MIMO) system. The method presented herein takes advantage of the modulation induced periodicities of the signals in the system and uses higher-order cyclostationary statistics to extract the signal and channel unknowns. This method can be used to identify more signals in the system than antenna elements at the receiver (overloaded case). This dissertation presents a system theoretic analysis of the problem as well as describes the development of an algorithm that can be used in the identification of the channel and the modulation of the signals in the system. Linear and non-linear receivers are examined at the beginning of the manuscript in order to review the a priori information that is needed for each receiver configuration to function properly. / Ph. D.

Identiferoai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/30060
Date29 December 2005
CreatorsDietze, Kai
ContributorsElectrical and Computer Engineering, Stutzman, Warren L., Davis, William A., Reed, Jeffrey H., Annamalai, Annamalai Jr., Russell, David L.
PublisherVirginia Tech
Source SetsVirginia Tech Theses and Dissertation
Detected LanguageEnglish
TypeDissertation
Formatapplication/pdf
RightsIn Copyright, http://rightsstatements.org/vocab/InC/1.0/
RelationBlind_Identification_Dietze.pdf

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