Service differentiation in multirate wireless networks with weighted round-robin scheduling and ARQ-based error control
Why this work is in the frame
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Bibliographic record
Abstract
The radio link-level delay statistics in a wireless network using adaptive modulation and coding (AMC), weighted round-robin (WRR) scheduling, and automatic repeat request-based error control is analyzed in this letter. WRR scheduling can be used for service differentiation similar to that achievable by using the generalized processor sharing scheduling discipline. The analytical framework presented in this letter captures physical and radio link-level aspects of a multirate multiuser wireless network (e.g., general fading model, AMC, scheduling, error control) in a unified way. It can be used for admission control and cross-layer design under statistical delay constraints. The analytical results are validated by simulations. Typical numerical results are presented, and their useful implications on the system performance are discussed.
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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 | 0.001 |
| 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