Increased Spectrum Utilisation in a Cognitive Radio Network: An M#x002F;M#x002F;1-PS Queue Approach
Bibliographic record
Abstract
A channel share scheme is proposed as a solution to the resource allocation problem in cognitive radio networks whereby two secondary users can occupy the same channel simultaneously with the primary user. The solution will increase utilisation thus freeing up much needed spectrum to accommodate many more users. Processor sharing techniques have been developed but have not been extensively applied in cognitive radio networks, specifically, the weighted head of line processor sharing scheme has the potential of improving spectrum usage in networks. In this paper, we propose using transmission power as the basis for the weighting parameter. We then develop the state transition matrices for the model using continuous time Markov chains. Queues are imposed on both secondary users. The model is evaluated through simulations done on various network conditions. The results show that the proposed model offers a significant improvement over an ordinary M#x002F;M#x002F;1 two priority system. The applications can lead to improved network efficiency by allowing more users to transmit within a network.
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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 | 0.001 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 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 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".