Traffic Engineering in BFWA Mesh Networks at Millimeter Wave Band
Bibliographic record
Abstract
Inherent difficulties in millimeter-wave radio operations, such as higher atmospheric attenuation, especially during rainy times, motivated the use of mesh architecture in millimeter-wave band for broadband fixed wireless access (BFWA) networks. When used with highly directional antennas, these mesh networks also provide better frequency reuse. A recent proposed architecture for such networks shows how a link can have multiple radio channels. This paper exploits this property to present a solution that uses distributed dynamic channel allocation (DDCA) to reconfigure the link capacities to achieve better Traffic Engineering. DDCA works by adding or removing channels from a link while satisfying interference constraints, based on current network conditions. The paper proposes a DDCA algorithm and then integrates it with routing. The distributed dynamic nature of the algorithm provides true scalability with fast and dynamic reconfiguration of the network. Simulation results show that the proposed solution provides better performance than solutions that employ a fixed channel allocation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".