Superposition network coded cooperation for wireless networks
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Cooperative diversity is an innovative approach to improve the reliability of communication. Although this technique is considered in the next‐generation mobile communication standards, it has its own challenges in practice. For example, in simultaneous transmission‐based cooperative protocols, perfect synchronisation of nodes is very hard to realise. The traditional time division multiple access method can simplify the synchronisation problems but leads to long transmission delays. In this paper, a low‐delay cooperative strategy is proposed for a network with multiple sources and a single destination, which requires only a simple type of synchronisation. In this technique, we use a combination of superposition coding and network coding; hence the name superposition network coded cooperation. For this strategy, good bounds are obtained for the probability of correct detection for general M‐PSK and M‐QAM modulation and are compared with simulation results. The results demonstrate improvement in error performance compared with other transmission schemes requiring the same transmission time as superposition network coded cooperation. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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