Efficient integration of multi-rate traffic for 3rd generation DS-CDMA systems
Bibliographic record
Abstract
We address the issue of efficient integration of multi-rate traffic supported by third generation DS-CDMA systems. We have previously proposed the notion of line rate (adjusted data rate before spreading) to incorporate traffic with a wide range of source rates. Each selected line rate will support a group of multi-rate traffic. We evaluate the impact of line rate(s) selection on the forward link capacity of a system with integrated/mixed-rate traffic. We first derive the methodology of evaluating the capacity of mixed-rate traffic in the forward link. Our focus is to investigate the effect of processing gain and activity factor (resulting from a selected line rate) on the capacity of different traffic types. We also address the issue of Walsh-Hadamard codes usage of different length (at each selected line rate) and its impact on line rate selection. Our analysis provides insight into the use of line rate(s) for traffic integration and optimal selection of line rate(s).
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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 | 0.001 | 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".