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K-distribution fading models for Bayesian estimation of an underwater acoustic channel

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dc.contributor.advisor James C. Preisig. en_US
dc.contributor.author Laferriere, Alison Beth en_US
dc.contributor.other Woods Hole Oceanographic Institution. en_US
dc.date.accessioned 2011-05-23T18:14:26Z
dc.date.available 2011-05-23T18:14:26Z
dc.date.copyright 2011 en_US
dc.date.issued 2011 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/63080
dc.description Thesis (S.M. in Electrical Engineering and Computer Science)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; and the Woods Hole Oceanographic Institution), 2011. en_US
dc.description Cataloged from PDF version of thesis. en_US
dc.description Includes bibliographical references (p. 113-114). en_US
dc.description.abstract Current underwater acoustic channel estimation techniques generally apply linear MMSE estimation. This approach is optimal in a mean square error sense under the assumption that the impulse response fluctuations are well characterized by Gaussian statistics, leading to a Rayleigh distributed envelope. However, the envelope statistics of the underwater acoustic communication channel are often better modeled by the K-distribution. In this thesis, by presenting and analyzing field data to support this claim, I demonstrate the need to investigate channel estimation algorithms that exploit K-distributed fading statistics. The impact that environmental conditions and system parameters have on the resulting distribution are analyzed. In doing so, the shape parameter of the K-distribution is found to be correlated with the source-to-receiver distance, bandwidth, and wave height. Next, simulations of the scattering behavior are carried out in order to gain insight into the physical mechanism that cause these statistics to arise. Finally, MAP and MMSE based algorithms are derived assuming K-distributed fading models. The implementation of these estimation algorithms on simulated data demonstrates an improvement in performance over linear MMSE estimation. en_US
dc.description.statementofresponsibility by Alison Beth Laferriere. en_US
dc.format.extent 114 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582 en_US
dc.subject Joint Program in Applied Ocean Science and Engineering. en_US
dc.subject Electrical Engineering and Computer Science. en_US
dc.subject Woods Hole Oceanographic Institution. en_US
dc.subject.lcsh Underwater acoustics Computer simulation en_US
dc.subject.lcsh Sound Speed Measurement en_US
dc.title K-distribution fading models for Bayesian estimation of an underwater acoustic channel en_US
dc.type Thesis en_US
dc.description.degree S.M.in Electrical Engineering and Computer Science en_US
dc.contributor.department Joint Program in Applied Ocean Science and Engineering. en_US
dc.contributor.department Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. en_US
dc.contributor.department Woods Hole Oceanographic Institution. en_US
dc.identifier.oclc 725923791 en_US


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