Bibliographic record
Abstract
In cognitive radio networks, a slotted time structure is widely adopted. Accordingly, the slot length is a factor that can largely affect the performance of cognitive radio networks. In this paper, a slot length configuration scheme is proposed. In the proposed scheme, we assume imperfect spectrum sensing. The spectrum sensing result is considered when configuring the slot length. Therefore, slots with different sensing results have different slot lengths. This setting fully takes into account the fact that the sojourn time of channel idle state and busy state are usually different. An optimization problem to find out the optimal slot length configuration is formulated (which maximizes the secondary throughput) and analyzed. In the formulated problem, primary activities are protected by limiting the percentage of time that the primary activities are interfered with, and the energy efficiency of the secondary system is guaranteed by limiting the percentage of time for spectrum sensing. After a theoretical analysis of the problem, an algorithm is proposed to solve it. In the case of perfect spectrum sensing, another algorithm with low complexity is developed to solve the problem. The numerical results demonstrate that, by having different slot lengths with different sensing results, largely improved performance can be achieved. Impacts of system parameters on the secondary system performance are also discussed.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".