| 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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Sahmel_PH_T_2011.pdf |
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