Bibliographic record
Abstract
This paper considers the use of a friendly full-duplex (FD) relay to increase the secrecy rate over a fading channel between the legitimate source and destination in the presence of a naive or informed eavesdropper. Naive eavesdropper can only decode the received signals either from the source or from the relay, while informed eavesdropper can overhear signals transmitted from both the source and relay. Accordingly, we compare the achievable secrecy rates of FD relay with traditional half-duplex (HD) relay in terms of the channel state information (CSI) between nodes, eavesdropper types, and the self-interference (SI) in FD-Relay. We consider the non-convex power allocation problems for the developed FD-relay to maximize the secrecy rate under the power constraints and develop an efficient iterative algorithm based on the difference-of-two-concave-functions (DC) programming. The analytical and simulation results confirm that FD relay offers significant improvements in the secrecy rate over the HD-Relay.
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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 | 0.000 | 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".