Cooperative forwarding for vehicular networks using positive orthogonal codes
Bibliographic record
Abstract
Reliable multi-hop forwarding in vehicular networks is required by many critical Intelligent Transportation System (ITS) safety applications. Cooperative vehicular multi-hop schemes achieve reliability using broadcast transmissions and multiple forwarding relays at each hop. However, packet duplication must be controlled to circumvent the broadcast storm problem. This paper proposes the Cooperative POC-based Forwarding (CPF) protocol, which extends the repetition-based POC-MAC protocol to handle multi-hop transmissions. Multiple cooperating relays at each forwarding hop schedule their transmissions to correspond to a single POC codeword. The transmission adhere to the transmission patterns of the POC-MAC. The proposed scheme exploits spatial diversity while mitigating the effect of hidden terminals on broadcast transmissions. By allocating separate POC-based schedules for multi-hop packets and the periodic broadcast of safety heartbeat packets, the CPF protocol reduces the interference between the two. A Markov model is presented for the end-to-end probability of reception of multi-hop packets. The performance of the CPF protocol is compared with other multi-hop schemes through ns-2 simulations.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".