QoS-Aware Power-Efficient Scheduler for LTE Uplink
Why this work is in the frame
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Bibliographic record
Abstract
The continuous increase of mobile data traffic has created a substantial demand for high data rate transmission over mobile networks. However, mobile devices are provided with small batteries that can be drained quickly by high data rate transmission. Motivated by the fundamental requirement of extending the battery utilization time per charge of mobile devices, this work presents two power-efficient schedulers for mixed streaming services in LTE uplink systems. Our objective is to minimize the total transmission power for all users. The proposed schedulers are subject to rate, delay, contiguous allocation, and maximum transmission power constraints. We first consider an optimal scheduler that uses binary integer programming (BIP). Then, we propose an iterative scheduler that performs a low-complexity greedy algorithm which solves the BIP problem. We compare the performance of the proposed schedulers to the proportional fair (PF) scheduler in terms of rate, delay, average transmission power and complexity. Simulation results show that the proposed schedulers offer a remarkable transmission power reduction as compared to the PF scheduler, and satisfy the QoS requirements.
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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