Optimized bandwidth allocation in broadband wireless access networks
Bibliographic record
Abstract
Abstract Towards satisfying the requirements of International Mobile Telecommunications–Advanced, both the Institute of Electrical and Electronics Engineers (IEEE) and Third Generation Partnership Project (3GPP) introduced revolutionary wireless technologies, exploiting advanced technologies and architectures. Both IEEE's 802.16 (Worldwide Interoperability for Microwave Access (WiMAX)) and 3GPP's Long Term Evolution have been introduced to accommodate the increasing demand for mobile services and applications. To realize the true potential of these technologies, however, opportunistic frameworks for radio resource management must be designed to exploit the adaptive nature of mobile traffic. The utility optimized quality‐of‐service (QoS) framework proposed in this paper for the mobile WiMAX networks achieves this objective. To maintain support for QoS guarantees, the framework capitalizes on the adaptive nature of WiMAX traffic by individually linking connections with a utility function designed to both uphold the end users’ perceived performance and determine bandwidth allocations by a search tree maximization algorithm. In doing so, bandwidth utilization is maximized for all active connections, and blocking and dropping probabilities for new and handover calls, respectively, are minimized. The framework is evaluated through an extensive simulation model and is shown to outperform state‐of‐the‐art solutions. Copyright © 2014 John Wiley & Sons, Ltd.
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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.006 | 0.006 |
| 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".