Neighbor discovery algorithms in directional antenna based synchronous and asynchronous wireless ad hoc networks
Why this work is in the frame
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Bibliographic record
Abstract
The performance of wireless systems could be significantly improved by directional antennas with highly efficient MAC layers and other control protocols and algorithms. One such critical algorithm is neighbor discovery, which establishes links between adjacent neighboring nodes in the network. In this article, we first study the slotted synchronous system and propose a novel neighbor discovery algorithm to address the high collision problem caused by high node density. We then evaluate the performance of neighbor discovery algorithms and extend the results to asynchronous systems. Simulation results show that for the synchronous system, our algorithm consistently shortens the required time for the whole discovery process from that in previous works; for an asynchronous system, our algorithm sheds insight on how to select design parameters.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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