On the Identification of SM and Alamouti-Coded SC-FDMA Signals: A Statistical-Based Approach
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Bibliographic record
Abstract
Signal identification represents the task of a receiver to identify the signal type and its parameters, with applications to both military and commercial communications. In this paper, we investigate the identification of spatial multiplexing and Alamouti space-time block codes with single-carrier frequency-division multiple-access signals, when the receiver is equipped with a single antenna. We develop a discriminating feature based on a fourth-order statistic of the received signal as well as a constant false-alarm rate decision criterion that relies on the statistical properties of the feature estimate. Furthermore, we present the theoretical performance analysis of the proposed identification algorithm. The algorithm does not require channel or noise power estimation, modulation classification, and block synchronization. Simulation results show the validity of the proposed algorithm as well as a very good agreement with the theoretical analysis.
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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 | 0.000 |
| 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