Towards secure communications in cooperative cognitive radio networks
Bibliographic record
Abstract
In this paper, a cooperative cognitive radio networking framework, which enhances the security of communications for the primary users (PUs) and provides transmission opportunities to secondary users (SUs), is proposed. Particularly, a PU selects two cooperating SUs, a relay SU and a jammer SU, for improving communication secrecy and grants a fraction of the bandwidth resource as a reward to the SUs, in which the cooperating SUs transmit their own data simultaneously using quadrature signaling. The objective of the cooperation is to maximize the secrecy rate of the primary link while satisfy the transmission rate requirements of SUs. To this end, the PU selects the best cooperating SUs and allocates the bandwidth optimally, while the relay and jammer SUs determine the optimal transmit power. Numerical results demonstrate that, with the proposed cooperative framework, the PU can achieve the maximum secrecy rate through cooperation with the selected SUs.
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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 | 0.001 | 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".