Performance Analysis of Common Radio Resource Management Scheme in Multi-Service Heterogeneous Wireless Networks
Why this work is in the frame
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Bibliographic record
Abstract
A major challenge of the heterogeneous wireless networks is how to jointly utilize the resources of different radio access technologies (RATs) in an efficient manner while simultaneously achieving the desired multi-service quality of service (QoS) and minimizing the service cost. To meet the challenge, this paper proposes an adaptive common radio resource management (CRRM) scheme in the context of wireless wide area network (WWAN) and wireless local area network (WLAN). The key parameters of the scheme are service type, user mobility and location information, load information, and service cost. The effectiveness of the proposed CRRM scheme is assessed analytically using the theory of Markov chains. Numerical results show that the proposed scheme minimizes the rate of unnecessary vertical handoffs (VHO), thereby providing stable communication without degrading call blocking performance and increasing service cost.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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