Cooperative networking towards secure communications for CRNs
Bibliographic record
Abstract
In this paper, we investigate cooperative networking in cognitive radio networks (CRNs), which targets to help the primary users (PUs) for secure communications and provide transmission opportunities to secondary users (SUs). Two cooperation schemes: relay-jammer (R-J) scheme and cluster-beamforming (C-B) scheme, are proposed. In R-J cooperation scheme, two individual SUs, a relay and a friendly jammer, are leveraged by the PU to improve communication secrecy via cooperation; In return, the PU allocates a fraction of access time for SUs' transmission. To achieve the maximum secrecy rate, joint time and power allocation is considered. In C-B cooperation scheme, the PU cooperates with a cluster of SUs, which enhance the secrecy of primary link via collaborative beamforming and gain spectrum access opportunities as a reward. With the objective of maximizing the secrecy rate, the optimal weights and time allocation are studied. Numerical results validate the proposed schemes and demonstrate that the PU can significantly enhances the secrecy through cooperation with the cooperating SUs by allocating time and transmission power optimally.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".