Performance of two-way multi-relay inter-vehicular cooperative networks
Bibliographic record
Abstract
Vehicle-to-vehicle (V2V) communications have recently received growing attentions due to the fact that it enables dynamic wireless data exchange between nearby vehicles, offering the opportunity for safety improvements and information sharing. In this paper, we investigate the performance analysis of a two-way amplify-and-forward (AF) multi-relay cooperative V2V communication networks with MPSK modulation, for two cases where the relays are vehicles or they are access-points of the road. In the mobile-to-mobile communication system considered in this paper, the communication channel is modeled as double-Rayleigh fading channel. We derive the exact symbol error probability (SEP) expressions under the two-phase and three-phase scenarios followed by their upper bound expressions. Then we examine the effect of the relays' position with respect to the source terminals, on their SEP and lastly, the maximum achievable diversity order under each scenario is studied.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".