On efficient power allocation modeling in virtualized uplink 3GPP-LTE systems
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Bibliographic record
Abstract
In order to accommodate mobile users' consumed power with the rapid increase of multimedia-rich mobile data, additional network capacities with optimized power allocation scheduling algorithms should be deployed. Motivated by the fundamental requirement of extending the mobile devices' battery utilization time per charge, this work formulates the optimized power allocation problem in a virtualized scheme considered in the third generation partnership project-long term evolution (3GPP-LTE) uplink (UL) systems. The proposed framework efficiently shares the evolved nodeB's dedicated physical radio resources blocks of service providers having different requirements under dynamic channel conditions. The objective is to minimize the total transmission energy for all users subject to exclusive and contiguous allocation, maximum transmission power, and rate constraints. Two algorithms are developed. A binary integer programming (BIP)-based algorithm is used to solve a simplified version of the problem. A heuristic algorithm is also presented that approaches the BIP-based algorithm's performance. Simulation results show that the proposed framework offers a remarkable transmission power reduction in the virtualized scenario as compared to the non-sharing one.
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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 | 0.000 |
| 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