An optimization framework for balancing throughput and fairness in wireless networks with QoS support
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Quality-of-service (QoS) provisioning, high system throughput, and fairness assurance are indispensable for heterogeneous traffic in future wireless broadband networks. With limited radio resources, increasing system throughput and maintaining fairness are conflicting performance metrics, leading to a natural tradeoff between these two measures. Balancing system throughput and fairness is desired. In this paper, we consider an interference-limited wireless network, and derive a generic optimization framework to obtain an optimal relationship of system throughput and fairness with QoS support and efficient resource utilization, by introducing the bargaining floor. From the relationship curve, different degrees of performance tradeoff between throughput and fairness can be obtained by choosing different bargaining floors. In addition, our framework facilitates call admission control to effectively guarantee QoS of. multimedia traffic. The solutions of resource allocation obtained from the optimization framework achieve the pareto optimality, demonstrating efficient use of network resources.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 it