Back to results

Rice University

Efficient Radiometric Signature Methods for Cognitive Radio Devices

Abstract

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.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
Masters
Discipline thesis:degree_discipline
Engineering
Grantor
Rice University
Year dc:date.issued
2011

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kocabas, Ovunc
Advisor dc:contributor.advisor
  • Koushanfar, Farinaz

Subjects

dc:subject × 2

Rights

dc:rights
Statement dc:rights
  • Copyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1911/70296
OAI identifier oai:identifier
oai:repository.rice.edu:1911/70296

Chain of custody

source
Harvested from
Rice University
Base URL
repository.rice.edu/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Kocabas, Ovunc. Efficient Radiometric Signature Methods for Cognitive Radio Devices. Masters thesis, Rice University, 2011. https://hdl.handle.net/1911/70296