Physical Layer Authentication Enhancement Using Two-Dimensional Channel Quantization
Why this work is in the frame
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Bibliographic record
Abstract
A novel physical layer authentication enhancement scheme is proposed in this paper by integrating multipath delay characteristics of wireless channels into the channel impulse response (CIR)-based physical layer authentication framework. In order to simplify the decision rule for authentication, a two-dimensional (2-D) quantization method is developed to preprocess the channel variations. More specifically, two one-bit quantizers are used to quantize the temporal channel variations in the dimensions of channel amplitude and path delay, respectively. Under a simple hypothesis testing, a new test statistic is developed based on the sum of outputs of the two quantizers. For performance analysis, false alarm rate (FAR) and probability of detection (PD) are defined based on the developed test statistic, and their closed-form expressions are derived as well. An optimization problem is defined for finding optimal parameters of the proposed scheme based on exhaustive search method. Monte Carlo simulations are utilized to evaluate the performance of the proposed scheme. Compared with other existing method in the literature, the proposed scheme outperforms significantly in spoofing detection.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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