Cooperative cognitive radio networking for opportunistic channel access
Bibliographic record
Abstract
In this paper, an opportunistic channel access for cognitive radio networks (CRNs) with multiple channels is proposed, whereby the secondary users (SUs) cooperate with primary users (PUs) to improve the latter's throughput and gain transmission opportunities in return. Cooperation on single channel is studied first, which is modeled by the Stackelberg game. By analyzing the game, the access time allocation of the PU and the optimal transmission power of the SU can be obtained. Then, based on the outcome of the above game, cooperation on multiple channels in the network is studied. To better exploit transmission opportunities on different channels, a cluster-based cooperation scheme (CBC) is proposed, whereby SUs first form a cluster, select best SUs to obtain the maximum sum of the access time using maximum weight matching, and then share the obtained channels fairly using congestion game and quadrature signalling. The condition for Nash Equilibrium (NE) of the congestion game is provided and an algorithm for CBC scheme is proposed. Numerical results demonstrate that, with the proposed scheme, the SUs can get more average access time and achieve higher fairness, compared with the random channel access approach.
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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 | 0.001 | 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".