Performance analysis of cognitive radio networks with channel assembling and imperfect sensing
Bibliographic record
Abstract
This paper investigates the performance of a wideband cognitive radio network where each cognitive user can assemble multiple primary channels. Two channel assembling schemes are considered: a constant channel assembling (CCA) and a variable channel assembling (VCA). In the variable channel assembling scheme, cognitive users assemble their channels on the basis of the number of detected residual channels that are unoccupied by primary users or cognitive users. The effects of imperfect spectrum sensing (with false alarms and misdetections) are taken into account and it is assumed that spectrum handover is implemented in the secondary network. These channel assembling schemes are analyzed by using Continuous-time Markov chains (CTMC), and the system performance is evaluated in terms of throughput, blocking probability, and forced termination probability. Numerical results show that channel assembling achieves lower forced termination probability, but does not increase achieved system throughput and leads to higher blocking probability. They also show that VCA outperforms CCA in terms of throughput and forced termination probability.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 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".