Optimal downlink scheduling schemes for CDMA networks
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Bibliographic record
Abstract
The problem of allocating radio resources in the downlink of a CDMA network is studied. The modulation and coding schemes, numbers of multicodes, and transmit powers used for all mobile stations (MS's) are jointly chosen so as to maximize the total transmission bit rate, subject to certain constraints. Based on the discrete and nonlinear nature of the proposed model, a mixed-integer nonlinear programming optimization problem is formulated. It is shown that the nonlinear relationship between bit rate and transmit power due to the use of different modulation and coding schemes and the maximum number of multicodes which can be assigned to an MS generally result in an optimal allocation which involves simultaneous transmission to several MS's. In addition, it is shown that the optimal scheduler can yield a significant improvement in throughput by taking the MS traffic loads into account.
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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