Channel modeling in wireless optical communications using Markov chains
Why this work is in the frame
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Bibliographic record
Abstract
Wireless optical communications is an attractive solution for the so-called ldquolast-milerdquo problem due to the ever-increasing demand for high-speed communications, and the difficulty of installing cable and optical fiber. In the presence of atmospheric phenomena such as cloud, fog, and turbulence the wireless optical communications channel happens to be time varying and dispersive, required to be accurately modeled. In most of the previous works, Monte-Carlo Ray Tracing (MCRT) algorithm has been used to measure channel parameters, though this algorithm needs a high computational capacity and a long execution time. We show that by modeling the photon trajectory in space by a Markov chain, angular dispersion can be calculated via matrix multiplications. We show that Markov chain model produces values that are close to MCRT algorithm results.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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