Radiometric identification of LTE transmitters
Why this work is in the frame
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Bibliographic record
Abstract
This paper demonstrates that highly accurate radiometric identification of Long Term Evolution (LTE) transmitters is possible using commercial off-the-shelf hardware and support vector machines (SVM). The identification is based on unique modulation characteristics exhibited by the transmitters, resulting from minute imperfections introduced during radio hardware manufacturing. In these experiments, the Agilent Vector Signal Analysis (VSA) software and the Agilent PXA spectrum analyzer are used to extract radiometric properties from several LTE base stations, known as evolved Node B (eNB). The open-source SVM library libsvm performs the classification using 13 feature coefficients extracted by the VSA. When SVM parameters are optimized using grid search, and the training bin contains no less than 45 vectors, re-identification is shown to be in excess of 98%.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it