VM2M: An overlay network to support Vehicular traffic over LTE
Bibliographic record
Abstract
We describe a Vehicular M2M (VM2M) overlay network over random access channel (RACH) in LTE that aims to emulate the control channel (CCH) of vehicular ad hoc networks (VANETs). VM2M overlay is implemented over a dedicated subset of preamble codes, at the physical layer, and uses a medium access control (MAC) layer modeled as IEEE 802.15.4 carrier sense multiple access (CSMA/CA) mechanism. We evaluate the performance and interaction of regular LTE (H2H) traffic and VM2M traffic, in particular the impact of RACH resource configuration and preamble format (PF) in large cells. We have found that the format PF = 2 is capable but not ideal for handling large amount of CCH traffic due to repeated preamble transmissions in H2H layer; better results may be obtained if the frequency of RACH subframe allocation for CCH is increased, or a larger number of preambles is used at the physical layer of CCH.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; both teacher heads agree on what is shown here.
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".