Adaptive admission/congestion control policies for CDMA-based wireless internet: Research Articles
Bibliographic record
Abstract
Radio resource management (RRM) is vital for the next generation wireless networks. RRM comprises many functionalities and this paper focuses on the investigation of the performance of several adaptive call admission/congestion control policies based on a window-measurement estimation of the status of the buffer at the base station under the hybrid TDMA/CDMA access scheme. In our study, we interrelate the physical limitations of the base stations (i.e. the number of transmission and reception modems), call and burst level traffic, instantaneous buffer conditions and end-to-end bit error performance in one queuing problem. Subsequently, a window-measurement estimator is implemented to estimate the likelihood of buffer congestion at the base station. Accordingly, the traffic loads shall be controlled. We use event-driven simulation to simulate the multimedia integrated CDMA networks where heterogeneous traffic users are multiplexed into a simple TDMA frames. The simulation results show outstanding performance of the proposed call admission/congestion control policies in guaranteeing QoS requirements. Copyright © 2005 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".