Secrecy Outage Probability and Secrecy Capacity for Autonomous Driving in a Cascaded Rayleigh Fading Environment
Bibliographic record
Abstract
Autonomous driving is a use case in 5G enhanced vehicle to vehicle (V2V) communication. Secure transmission of V2V messages is paramount for the successful deployment and operation of autonomous vehicles, especially in the presence of passive eavesdroppers. The secrecy outage probability and instantaneous secrecy capacity necessary for successful V2V communication in a cascaded Rayleigh fading environment are assessed. An algorithm for selecting the appropriate vehicle to serve as a relay to achieve secure dual-hop communication between a legitimate transmitter and a legitimate receiver in the presence of a passive eavesdropper is proposed. The simulation and analytical results are compared. Numerical results show that the relay selection algorithm can successfully be used in dual hop communications. Results suggest that designers of V2V communication should consider fading techniques outside of the traditional single Rayleigh.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".