Show simple item record

dc.contributor.advisor Koushanfar, Farinaz
dc.creatorKocabas, Ovunc
dc.date.accessioned 2013-03-08T00:35:09Z
dc.date.available 2013-03-08T00:35:09Z
dc.date.issued 2011
dc.identifier.urihttps://hdl.handle.net/1911/70296
dc.description.abstract This thesis presents the first comprehensive study and new methods for radiometric fingerprinting of the Cognitive Radio (CR) devices. The scope of the currently available radio identification techniques is limited to a single radio adjustment. Yet, the variable nature of the CR with multiple levels of parameters and adjustments renders the radiometric fingerprinting much more complex. We introduce a new method for radiometric fingerprinting that detects the unique variations in the hardware of the reconfigurable radio by passively monitoring the radio packets. Several individual identifiers are used for extracting the unique physical characteristics of the radio, including the frequency offset, modulated phase offset, in-phase/quadrature-phase offset from the origin, and magnitude. Our method provides stable and robust identification by developing individual identifiers (classifiers) that may each be weak (i.e., incurring a high prediction error) but their committee can provide a strong classification technique. Weighted voting method is used for combining the classifiers. Our hardware implementation and experimental evaluations over multiple radios demonstrate that our weighted voting approach can identify the radios with an average of 97.7% detection probability and an average of 2.3% probability of false alarm after testing only 5 frames. The probability of detection and probability of false alarms both rapidly improve by increasing the number of test frames.
dc.format.extent 72 p.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.subjectApplied sciences
Electrical engineering
dc.title Efficient Radiometric Signature Methods for Cognitive Radio Devices
dc.identifier.digital KocabasO
dc.type.genre Thesis
dc.type.material Text
thesis.degree.department Electrical and Computer Engineering
thesis.degree.discipline Engineering
thesis.degree.grantor Rice University
thesis.degree.level Masters
thesis.degree.name Master of Science
dc.identifier.citation Kocabas, Ovunc. "Efficient Radiometric Signature Methods for Cognitive Radio Devices." (2011) Master’s Thesis, Rice University. https://hdl.handle.net/1911/70296.


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record