An opportunistic-based protocol for bidirectional cooperative networks
Bibliographic record
Abstract
In this paper, a new opportunistic source selection (OSS) protocol is studied in bidirectional cooperative networks. Unlike existing protocols, this protocol exploits multiuser nature of the bidirectional cooperative networks and it opportunistically supports two traffic flows based on instantaneous channel conditions. This makes the OSS protocol much more reliable than existing protocols. In order to show the performance improvement, we first derive a lower bound of the outage probability of the OSS protocol. Numerical results demonstrate that this lower bound is extremely tight and it indicates that the OSS protocol achieves full diversity order two in a bidirectional cooperative network with two sources and one relay. Then exact and approximate lower bounds of average bit error rates (BERs) at both sources in the OSS protocol are derived. Those lower bounds are very close to the exact average BERs as shown by numerical results. Lastly, an optimum power allocation scheme is developed for the OSS protocol. This scheme can optimize the outage probability, average BER, and data-rate of the OSS protocol at the same time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".