Capacity enhancement of Web traffic in W-CDMA mobile satellite systems
Bibliographic record
Abstract
We attempt to enhance the Web traffic capacity of third generation (3G) W-CDMA land mobile satellite communication systems. The aim of the capacity analysis is first to analyze the effect of power control errors (PCEs) which are expected to degrade the performance of mobile satellite systems severely (see Hijres Alsuwaidi, J. and Mahmoud, S.A., 2001). Secondly, the use of macrodiversity, as proposed to mitigate the effect of power control errors (see Hijres Alsuwaidi and Mahmoud, Globecom, 2002), is shown to be a very powerful method to enhance the Web traffic capacity of multi-beam GEO and MEO mobile satellite systems. Numerical results indicate that macrodiversity may be considered as an essential component to enhance Web traffic capacity of power limited 3G mobile satellite systems, hence lowering the channel operation cost which can be considered as the main challenge in deploying 3G mobile satellite systems.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".