Interference Management in WLAN Mesh Networks Using Free-Space Optical Links
Bibliographic record
Abstract
Frequency channels are assigned in wireless local-area network (WLAN) mesh networks subject to strict cochannel interference constraints. Since Wi-Fi may be freely used by other networks, added interference may eventually invalidate the original frequency assignment, making full link activation impossible. In this paper, we address this problem by selectively installing supplementary free-space optical (FSO) links when radio-frequency (RF) link performance has deteriorated. To minimize cost, the number of FSO links that are needed should be as small as possible. We first formulate the channel assignment problem with the objective of maximizing the number of simultaneous link activations while satisfying cumulative RF interference constraints. A proof is given for the NP-completeness of the joint frequency assignment and FSO link placement problem. We then propose an efficient heuristic to solve the channel assignment problem using a genetic algorithm. Results are then presented for various mesh networks which show that the proposed algorithm has good results compared with the computed bounds. The presented results show that the use of FSO links permits WLAN mesh network deployment in interference-prone situations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".