Performance Analysis for RUB-Based Cognitive Radio Network with Cooperative Beam Selection
Bibliographic record
Abstract
This paper studies the performance of a RUB-based cognitive radio (CR) network, which coexists with a primary network with single primary transmitter (PT) and single primary user (PU). It is assumed that the PU can control the availability of each beam of the secondary base station (SBS) over a feedback link. The PU only needs to feed back to the SBS the index of the usable beams, which lead to the received SINR at the PU larger than a predefined beam selection threshold, and the outage probability of the primary system can be limited to a tolerable level. The SBS then selects one from the usable beams to achieve the largest throughput of the secondary system. We derive the accurate upper bound of the outage probability of the primary system and the exact throughput of the secondary system. Numerical examples show that to avoid the burst increase of the outage probability of the primary system, as well as achieve the maximal throughput of the secondary system, the beam selection threshold should be equal to the outage threshold of the primary system.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".