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dc.contributor.authorClark, William H. IVen
dc.date.accessioned2015-06-04T14:54:45Zen
dc.date.available2015-06-04T14:54:45Zen
dc.date.issued2015en
dc.identifier.urihttp://hdl.handle.net/10919/52908en
dc.description.abstractThis paper proposes a cumulant based classification means to identify waveforms for a blind receiver in the presence of time varying channels, which is built from the work done on cumulants in static channels currently in the literature. Results show the classification accuracy is on the order or better than current methods in use in static channels that do not vary over an observation period. This is accomplished by making use of second through tenth order cumulants in a signature vector that the search engine platform has the means of differentiating. A receiver can then blindly identify waveforms accurately in the presence of multipath Rayleigh fading with AWGN noise. Channel learning occurs prior to classification in order to identify the consistent distortion pattern for a waveform that is observable in the signature vector. Then using a database look-up method, the observed waveform is identified as belonging to a particular cluster based on the observed signature vector. If the distortion patterns are collected from a variety of channel types, the database can then classify both the waveform and the rough channel type that the waveform passed through. If the exact channel model or channel parameters is known and used as a limiter, significant improvement on the waveform classification can be achieved. Greater accuracy comes from using the exact channel model as the limiter.en
dc.language.isoenen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectcommunicationsen
dc.subjectmodulation classificationen
dc.subjectcumulanten
dc.subjectsearch engine platformen
dc.titleBlind Comprehension of Waveforms through Statistical Observationsen
dc.typeThesisen
dc.contributor.departmentElectrical Engineeringen
dc.description.degreeMaster of Scienceen
thesis.degree.nameMaster of Scienceen
thesis.degree.levelmastersen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.disciplineElectrical Engineeringen
dc.contributor.committeechairMcGwier, Robert W.en
dc.contributor.committeememberClancy, Thomas Charles IIIen
dc.contributor.committeememberBuehrer, R. Michaelen


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