Multi-class bandwidth allocation policy for 3g wireless networks
Why this work is in the frame
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Bibliographic record
Abstract
In this paper we develop an analytical threshold-based bandwidth allocation policy for 3G multi-class cellular networks. We consider the effects of user mobility when the cellular network supports multiple classes of connections having different QoS bandwidth requirements. The policy gives priority to handoff connections over new calls and prioritizes between different classes of handoff connections according to their QoS constraints by assigning a maximum occupancy, i.e. a threshold, to each connection class. The policy can be modeled as a multi-dimension Markov chain, and therefore, a product farm solution is provided. The QoS metrics - new call blocking probability, handoff call dropping probability, and probability of unsuccessful call completion are derived. We show numerically that this policy improves the service quality by minimizing handoff dropping probability and maximizing the bandwidth utilization i.e. by minimizing the new call blocking probability.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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 it