Maximizing Throughput with Multiple Power Levels in a Random Access Infrastructure-Less Radio System
Bibliographic record
Abstract
We propose and analyse a new random access protocol with multiple power levels selection schemes for infrastructureless wireless networks. In these networks, mobile nodes may communicate with each other without a central entity (base station), where each mobile node will be either in a transmitting mode or in a receiving mode or in an idle mode. Throughput with random power levels selection scheme is derived in terms of the transmission probability of each mobile node, receiving probability of each mobile node and the number of power levels. Throughput with optimum power levels selection scheme is also derived and compared with the previous one. Results show that the optimum transmission probability of each mobile node to achieve the maximum throughput depends only on the number of power levels. The maximum throughput region is devised in terms of transmission probability of each mobile node and the number of power levels. The proposed new random access protocol is truly distributive in nature and can be easily implemented in infrastructure-less wireless access systems without requiring any centralized control.
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".