Minimum Selection GSC with Adaptive Modulation and Post-Combining Power Control
Why this work is in the frame
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Bibliographic record
Abstract
We consider the problem of finding low-complexity, bandwidth-efficient, and processing-power efficient transmission schemes for a downlink scenario under the framework of diversity combining. Capitalizing on recent results for joint adaptive modulation and diversity combining schemes (AMDC), we design and analyze two AMDC schemes that utilize power control to reduce the radiated power, and thus the potential interference to other systems/users. Based on knowledge of the channel fading, the proposed schemes adaptively select the signal constellation, diversity combiner structure, and transmit power level. We show that the novel schemes also provide significant average transmit power gains compared to existing joint adaptive QAM and diversity schemes. In particular, over a large signal to noise ratio range, the transmitted power is reduced by 30-50%, yielding a substantial decrease in interference to co-existing systems/users, while maintaining high average spectral efficiency, low combining complexity, and compliance with bit error rate constraints.
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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