An Adaptive Frequency Hopping TechniqueWith Application to Bluetooth-WLAN Coexistence
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Bibliographic record
Abstract
In this paper, a new adaptive frequency hopping (AFH) technique is proposed in an attempt to mitigate the interference between Bluetooth (IEEE 802.15) and wireless local area networks (WLANs) (IEEE 802.11b). The new AFH technique optimizes the carrier spacing according to the network load and noise level. For a given overall bandwidth and data rate, reducing the separation between adjacent channels has a positive effect of increasing the number of available hopping channels. This can definitely lead to decreasing the collision rate. On the other hand, decreasing the channel spacing increases the adjacent channel interference. Therefore, there exists an optimal channel spacing that maximizes the network throughput. Rayleigh fading was considered and results show that the new AFH technique outperforms existing AFH techniques for a wide range of network loads.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 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