A quadrature signaling based cooperative scheme for Cognitive Radio Networks
Bibliographic record
Abstract
A two-phase cooperative framework in Cognitive Radio Networks (CRNs), whereby the secondary users (SUs) can fully exploit the transmission opportunities through cooperation with primary users (PUs), is proposed. Specifically, the SU cooperates with the active PU to improve the PU's utility. As a reward, the period of time when the PU is inactive, is allocated to the cooperating SU for its own transmissions. During the cooperation, the PU and the cooperating SU use quadrature amplitude modulation (QAM) to attain orthogonal signaling to cooperate efficiently, while the SU selects the optimal power allocation coefficient to maximize the performance of the PU, when its own transmission requirement is satisfied. The SU selection and power allocation determination procedure is formulated as a nonlinear optimization problem. The closed-form solution is derived. Numerical results demonstrate that, with the proposed cooperative strategy, the PU can achieve optimal performance and the SU can gain transmission opportunities through cooperation.
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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 | 0.000 | 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".