Power Allocation and Scheduling for MAC Layer Design in UWB Networks
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Bibliographic record
Abstract
This paper proposes a practical joint power allocation and scheduling scheme for medium access control (MAC) layer design in ultra-wideband (UWB) networks. The scheme increases system spectral efficiency and reduces power consumption by fully considering the properties of the UWB, such as its capacity in supporting parallel transmission and providing accurate positioning, and its stringent constraint on computational complexity. Practical implementations of the proposed scheme are achieved by introducing a margin based power allocation scheme and an exclusive region based scheduling scheme. The margin based power allocation scheme is carried out based on each link's own information, and is simple to implement, while the exclusive region based scheduling scheme takes into account the interaction among different links. Simulation results show that the proposed power allocation and scheduling schemes exhibit good performance in terms of the average number of slots per frame and the power consumption reduction.
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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