On the receive power allocation in a cellular multimedia CDMA system with fixed base station assignment
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Bibliographic record
Abstract
In this paper, we consider the receive power allocation (RPA) problem for multimedia users in a cellular CDMA network. It is shown that the problem can be split into two optimization problems, source-based RPA (SBRPA) and network-based RPA (NBRPA). SBRPA determines the relative receive power levels (RPLs) between different classes of users in each cell irrespective of the intercell interference and it is locally implemented. NBRPA determines the relative RPLs between cells and can be achieved solving an eigenvalue problem with the system-wide class-wise SIR-balancing and it is globally implemented. The need for interference-balancing to increase the capacity with minimum mobile transmit power is emphasized. Finally, numerical results are presented to demonstrate the effectiveness of the proper RPA in a cellular multimedia CDMA system.
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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 | 0.001 | 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 | 0.001 | 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 it