A Semi-Supervised QPSO-TR PAPR Reduction Scheme for OTSM Systems
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Bibliographic record
Abstract
This paper proposes a semi-supervised quantum particle swarm optimization-based tone reservation (SS-QPSO-TR) method with affinity propagation (AP) clustering and k-nearest neighbours (KNN) algorithms. The proposed SS-QPSO-TR method reduces the high peak-to-average power ratio (PAPR) in orthogonal time sequency multiplexing (OTSM) systems. The main finding is a significant 4.5 dB, 4.3 dB and 4 dB PAPR reduction in contrast to the original OTSM for QAM-64, 16 and 4, respectively while concurrently reducing transmission computational complexity by 16.7 times, compared to adapted tone reservation in both-domain (A-TR-BD), at the same bit error rate (BER) and error vector magnitude (EVM) performance. The proposed SS-QPSO-TR scheme enables efficient modulation of OTSM transmitters in high-mobility, real-time, wireless communication scenarios.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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