Optimal Relay Selection for Secure Cooperative Communications With an Adaptive Eavesdropper
Why this work is in the frame
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Bibliographic record
Abstract
Optimal relay selection is investigated for secure cooperative communications against an adaptive eavesdropper that can perform eavesdropping if the eavesdropping link has good channel quality or perform jamming otherwise. A number of decode-and-forward relays are available for legitimate communications, among which one relay can be selected to help. For legitimate communications, three cases for availability of the eavesdropping channel information are considered: full channel knowledge, partial channel knowledge, and statistical channel knowledge. An optimal relay selection scheme is proposed for each case. For the first and third cases, exact secrecy outage probability expressions in closed form are derived, and for the second case, an approximate secrecy outage probability is derived, which is tight in the high main-to-eavesdropper ratio regime. Moreover, secrecy diversity order for the proposed relay selection scheme in each case is also derived, which is shown to be a full secrecy diversity. Finally, numerical results are given to verify the theoretical analysis derived in this paper.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| 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 it