Monte-Carlo Integration Models for Multiple Scattering Based Optical Wireless Communication
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Bibliographic record
Abstract
Monte-Carlo models are analyzed for multiple scattering channels in optical wireless communications. It is demonstrated that the system impulse response function can be obtained by Monte-Carlo integration model. The convergence performance for the Monte-Carlo integration model is analyzed and improved by introducing different sampling methods. The simulation results show that the gamma function model for channel impulse response function can only be applied to the cases where the common volume between the transmitted light beam and the receiving field-of-view is open. Numerical simulation suggests that for a three-order scattering case, the computation efficiency of the Monte-Carlo integration model based on partial importance sampling is about 12 times of the original Monte-Carlo integration model based on uniform sampling, and 5.6 times of the widely used Monte-Carlo simulation model. The numerical results also show that the Monte-Carlo integration model based on partial importance sampling has higher computation efficiency than the Monte-Carlo simulation model in a higher-order scattering communication scenario.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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