An RSU Controlled IEEE 802.11ac Based MAC Protocol for Multi-Vehicle Uplink Transmission in VANET
Bibliographic record
Abstract
In this paper, we have explored the possibility of using IEEE 802.11ac as the MAC layer solution for VANET to meet the new requirements for various types of broadband services for Vehicle to Infrastructure (V2I) wireless communication. We have proposed an efficient RSU controlled MAC protocol that enables uplink MU-MIMO transmission for different priority traffic categories. Performance metrics show that the throughput enhancement of proposed MAC in MU-MIMO uplink transmission is three times the throughput of a single user transmission. We observe that due to smaller contention window size, the mean backoff time for the highest priority messages remain in the range of millisecond even at high packet arrival rate and node density. The saturation throughput analysis clearly shows two desired operating points: highest network throughput and highest network capacity. We achieve a maximum payload throughput of 64% at an aggregate packet arrival rate of 1100 packets/sec whereas 54% network throughput is achieved at a maximum load of 1200 packets/sec. We observe that the stable operating load remains between 1100-1200 packets/sec in our model.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".