An adaptive protocol for cooperative communications achieving asymptotic minimum symbol-error-rate
Bibliographic record
Abstract
This paper investigates the protocol design issue for cooperation systems in wireless communications. A tight approximate symbol error rate (SER) for such systems is derived and analyzed. Based on such analysis, an optimum power allocation scheme is proposed by optimizing the derived approximate SER subject to fixed transmission rate and total transmit power constraints. Then, a novel adaptive protocol is proposed for cooperative communications based on minimizing the asymptotic SER (i.e. in an averaging sense under high-enough SNR regimes) of such systems. This proposed adaptive protocol is able to achieve the maximum achievable diversity gain available in such systems without sacrificing any transmission rate or the total transmit power, and optimally adapts the number of cooperation partners under the changing environments. Simulation results show that the proposed adaptive protocol provides a lower SER compared with existing protocols. In addition, the proposed adaptive protocol with optimum power allocation can remarkably enhance the SER performance in comparison with the equal power allocation scheme.
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How this classification was reachedexpand
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 | 0.001 |
| Open science | 0.003 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".