Channel Requirements for Interference-Free Wireless Mesh Networks to Achieve Maximum Throughput
Bibliographic record
Abstract
In a multi-radio multi-channel wireless mesh network, a channel assignment that is based on a fixed number of available frequency channels may cause co-channel interference, which degrades the network throughput. We address this problem by ensuring interference-free communication among the mesh nodes. The main purpose of this work is to determine the minimum number of non-overlapping frequency channels required for interference-free channel assignment in order to achieve the maximum network throughput while maintaining fairness among the multiple network flows, given the location of the mesh nodes and the number of their half-duplex radio interfaces. To minimize the number of channels required, we apply our Select x for less than x Topology Control Algorithm to build the connectivity graph instead of using the classical approach based on maximum power (MP). We show that our approach outperforms the MP-based approach in terms of the number of channels required as well as the links to channels ratio for all node-degrees.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.002 |
| 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".