On the impact of mobility and soft vertical handoff on voice admission control in loosely coupled 3G/WLAN networks
Bibliographic record
Abstract
Loose coupling between 3G and WLAN ensures flexibility and openness. However, providing an ubiquitous mobile voice service in a loosely coupled 3G/WLAN network requires both packet-level and call-level quality of service (QoS) guarantees using soft vertical handoff (SVHO) and call admission control (CAC). In this paper, we evaluate the impact of both SVHO and WLAN mobility on call blocking and dropping probabilities rederived for the integrated network. For this purpose, we propose a new multi-region mobility model that accurately estimate these probabilities under a resource-efficient dynamic threshold SVHO compared to a standard static-threshold SVHO. Results show us that the resource-efficient SVHO blocks and drops much less voice calls than the static one when very low mean and high variability of multi-mode mobile station velocities are noticed. Therefore, resource-efficient SVHO implementations are highly recommended in these mobility environments.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".