Energy efficient uplink resource allocation in a heterogeneous wireless medium
Why this work is in the frame
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Bibliographic record
Abstract
This paper investigates energy efficient uplink communications for battery-constrained mobile terminals (MTs). We consider a heterogeneous wireless medium where MTs communicate with base stations (BSs) and access points (APs) of different networks with overlapped coverage. Unlike the existing research, we develop a joint bandwidth and power allocation framework that maximizes energy efficiency for a set of MTs, in different service areas, with best effort service and multi-homing capabilities. The problem formulation captures the heterogeneity of the medium, in terms of different service areas, channel conditions, available resources at BSs/APs of different networks, and different available maximum power at the MTs. In addition, the framework is implemented in a decentralized manner which is desirable in a case that different networks are operated by different service providers. Simulation results are presented to demonstrate the performance of the proposed framework.
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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