On the Power Allocation for Decode-and-Forward Cooperative Transmission Over Rayleigh-Fading Channels
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Bibliographic record
Abstract
As an accompany paper [1], efficient power allocation strategies for cooperative transmission applying decode-and- forward (DF) approach are further investigated in this paper. The cooperative ratio, defined as the ratio of the power used for cooperative-information transmission to the total power, is investigated in an attempt to minimize bit error rate (BER) with a constraint of fixed total transmit power for each user. Our results show that efficient power allocation greatly depends on the cooperative method. The preferred cooperative ratio changes from low to high by using DF with no parity check, amplify-and-forward, DF with parity check. Simulation results show that with appropriate power allocation, BER performance of all cooperative schemes can achieve a significant gain over non-cooperative systems.
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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 | 0.001 | 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 | 0.001 | 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