Cross‐layer aware joint design of sensing and frame durations in cognitive radio networks
Bibliographic record
Abstract
The tradeoff between increasing secondary users’ (SUs’) throughput and decreasing interferences to primary user (PU) is an important problem in cognitive radio networks. Joint design of sensing duration and frame duration has a crucial impact on both these two conflicting attributes but has not been studied yet. In this study, using a cross‐layer approach, the authors investigate joint design of sensing duration and frame duration for the tradeoff. Specially, they consider that PU's traffic randomly changes within a secondary frame and multiple SUs contend to use the licensed channel based on widely used large/small‐scale‐backoff‐based MAC protocols. By modelling more realistic PU's traffic, imperfect spectrum sensing in PHY and multiple SUs’ access contention in MAC, the authors reformulate the sensing‐throughput tradeoff problem to maximise SUs’ throughput while restricting interference probability to PU under a tolerable level. Moreover, the optimal solution is analysed and a bi‐dimensional search algorithm is presented. Simulation results show that the authors’ proposal achieves better throughput performance than conventional approaches. They also show how the optimal solution varies with received PU's signal‐to‐noise ratio and PU's traffic distribution.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".