Towards QoS Assurance with Revenue Maximization of LTE Uplink Scheduling
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Qos provision is considered as the complex task due to the heterogeneous nature, diverse QoS requirements of emergent different applications. With the advent of high bandwidth 3G/4G technologies, like LTE, LTE-advanced, the necessity of QoS provision becomes even crucial. Uplink scheduling with QoS provision is considered here. The contribution of this work is uplink packet scheduling scheme maintaining QoS provision at the granular level while maximizing the revenue of network operator. Proposed scheme is generalized for all kinds of traffic. In order to demonstrate the results, we limit the classifications of traffic to best effort, traffic with delay requirement and traffic with bandwidth requirement. Through extensive simulation, we have justified the effectiveness and strength of the proposed scheme.
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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 | 0.000 | 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) | 0.000 | 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