A channel-based mobile-assisted fairly-shared packet scheduling scheme for nonreal-time applications in CDMA networks
Bibliographic record
Abstract
In this paper, we propose a fair packet scheduling scheme called CB+MA+FS for nonreal-time applications in a cellular CDMA network. Our research is motivated by the need to provide increased throughput in downlinks of a cellular CDMA system while ensuring fairness to users in terms of delivered throughput over time. The following packet scheduling schemes are investigated in this paper: channel based only (CBO), channel based and proportional fairness (CB+PF), and the proposed channel-based mobile-assisted and fairly-shared (CB+MA+FS). An indicator is used to decide the packets to be scheduled in each slot based on realtime channel conditions, required E/sub b//I/sub 0/, required average rate and achieved average rate. For each user, base station computes this indicator and ranks all users based on this indicator. Then, a certain percentage of users is scheduled based on the current link states and achieved average throughput.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 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".