Title page for ETD etd-12062011-095822


Type of Document Master's Thesis
Author Sahmel, Peter H
Author's Email Address phsahmel@vt.edu
URN etd-12062011-095822
Title Eigenspace Approach to Specific Emitter Identification of Orthogonal Frequency Division Multiplexing Signals
Degree Master of Science
Department Electrical and Computer Engineering
Advisory Committee
Advisor Name Title
Reed, Jeffrey Hugh Committee Chair
Dietrich, Carl B. Committee Member
Spooner, Chad M. Committee Member
Keywords
  • Cyclostationarity
  • Eigenecomposition
  • Hidden Markov Models
  • Specific Emitter Identification
Date of Defense 2011-11-16
Availability unrestricted
Abstract
Specific emitter identification is a technology used to uniquely identify a class of wireless devices, and in some cases a single device. Minute differences in the implementation of a wireless communication standard from one device manufacturer to another make it possi- ble to extract a wireless ”fingerprint” from the transmitted signal. These differences may stem from imperfect radio frequency (RF) components such as filters and power amplifiers. However, the problem of identifying a wireless device through analysis of these key signal characteristics presents several difficulties from an algorithmic perspective. Given that the differences in these features can be extremely subtle, in general a high signal to noise ratio (SNR) is necessary for a sufficient probability of correct detection. If a sufficiently high SNR is not guaranteed, then some from of identification algorithm which operates well in low SNR conditions must be used. Cyclostationary analysis offers a method of specific emitter iden- tification through analysis of second order spectral correlation features which can perform well at relatively low SNRs. The eigenvector/eigenvalue decomposition (EVD) is capable of separating principal components from uncorrelated gaussian noise. This work proposes a technique of specific emitter identification which utilizes the principal components of the EVD of the spectral correlation function which has been arranged into a square matrix. An analysis of this EVD-based SEI technique is presented herein, and some limitations are identified. Analysis is constrained to orthogonal frequency division multiplexing (OFDM) using the IEEE 802.16 specification (used for WiMAX) as a guideline for a variety of pilot arrangements.
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