Secrecy Performance of Dual-Hop Threshold Relaying System with Diversity Reception
Bibliographic record
Abstract
In this paper, the secrecy of a cooperative system consisting of a single source, relay, destination and eavesdropper is analyzed. The threshold-selection decode-and-forward relay is considered, where the relay can correctly decode and forward only if it satisfies a threshold signal-to-noise ratio (SNR). Both destination and eavesdropper take advantage of the direct and relayed transmissions through maximal ratio diversity combining. The secrecy outage probability (SOP) and ergodic secrecy rate are derived in closed-form for different channel state information (CSI) availability. It was observed that when the required rate is low, having CSI knowledge is more advantageous than in the case of higher rate. An increase in the required threshold SNR at the relay can increase the SOP if the relayed link SNR is relatively higher than the direct link SNR. It was also shown that SOP cannot be improved beyond a certain value when keeping either dual-hop link average SNR fixed and increasing the other link SNR, whereas the ergodic secrecy rate can be increased by keeping the source to destination average SNR fixed.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".