Service-Aware Optimal Spectrum Sharing Algorithm in Heterogeneous Wireless Networks
Why this work is in the frame
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Bibliographic record
Abstract
Due to the heterogeneity and versatility of emerging services and applications in wireless networks, it has been a great challenge on improving the network utility by taking advantage of the spatial and temporal diversity of radio resource consumption. This paper is committed to solving this problem by introducing a service-aware spectrum sharing algorithm (SSA) in a joint radio resource management (JRRM) architecture, where a spectrum pool is adopted for leisure spectrum resource management in heterogeneous wireless networks. Based on an objective utility function, the JRRM unit could optimize the spectrum scheduling decisions for the composing networks with awareness of the related supporting services. Moreover, to facilitate a precise decision process, we illustrate an transmission rate requirement prediction model (TRPM) that is adaptive to the system condition variants to forecast service requests. Experiment results show that the proposed SSA can solidly enhance the system performance in terms of radio resource usage ratio, system throughput, user service access ratio, and eventually achieve better network utility.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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