Relay selection in cognitive radio networks with interference constraints
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Bibliographic record
Abstract
In this study, the authors investigate the outage probability of underlay cognitive radio systems with relay selection. In particular, they consider a secondary multi‐relay network operating in the amplify‐and‐forward (AF) mode and only the ‘best’ relay is selected, which satisfies an index of merit. The proposed selection strategy takes into consideration the effect of primary user (PU) interference. That is, the authors assume that the secondary multi‐relay network is exposed to unwanted interference from a neighboring PU network. They derive a closed‐form outage probability expression and further present a thorough asymptotic diversity order analysis of the underlying scenario. A simulation study is presented to corroborate the analytical results and to have further insight into the performance of the proposed selection strategy.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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