On Maintaining Multimedia Session's Quality in CDMA Cellular Networks Using a Rate Adaptive Framework
Bibliographic record
Abstract
In T. Kwon et al. (2003) the authors have developed call admission control and adaptive bandwidth allocation schemes for serving multimedia connections in cellular wireless networks with fixed cell capacity. The architecture considers an adaptive networking framework where the bandwidth of multimedia calls can be dynamically adjusted, and the proposed admission method works by enforcing an upper bound on the cell overload probability. In this paper we consider a similar adaptive framework, and devise call admission control and bandwidth allocation strategies to serve multimedia connections in a CDMA-based 3G cellular network. The architecture aims at maintaining the session's quality during both intra-cell and inter-cell user movements by limiting the cell overload probability. A novel aspect of our work is a method for exploiting a priori knowledge of user mobility patterns to estimate the cell overload probability after some prescribed prediction interval. Important properties of the devised method are proved analytically. Compared to a non-predictive admission control scheme, the obtained results show that the proposed scheme achieves a lower forced termination probability, and higher throughput while consuming less base station transmission energy
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".