A Maximum-Throughput Call Admission Control Policy for CDMA Beamforming Systems
Bibliographic record
Abstract
A throughput-maximization call admission control (CAC) policy is proposed for CDMA beamforming systems in which the QoS requirements in both physical and network layers can be guaranteed. While the existing cross-layer CAC policies rely on a separate reduced-outage-probability (ROP) algorithm to guarantee the physical layer QoS requirement, which adds to system complexity and reduces spectral efficiency, the proposed CAC policy can maintain arbitrary outage probability constraints as well as all the other QoS requirements without the aid of any ROP algorithm. The optimal CAC policy, obtained by formulating a constrained semi-Markov decision process (SMDP), is able to optimize the overall system throughput across different layers. Numerical examples demonstrate that the proposed policy is capable of achieving a significant performance gain, in terms of lowered blocking and outage probabilities as well as increased system throughput.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.002 | 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".