Diversity and Multiplexing for Near-Field Atmospheric Optical Communication
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, the performance of multi-beam free-space optical (FSO) communication systems are studied through an accurate analytical approach which does not rely on far-field assumptions commonly used in the literature. A framework is presented for analytical and numerical performance analyses of multi-beam FSO systems employed in a diversity or multiplexing scheme. The performance analyses show that the far-field assumptions may not correctly estimate the system behavior in many geometrical scenarios within practical interest. The results demonstrate the degrading effects of diffraction and spatial correlation of atmospheric turbulence in the form of diversity gain reduction in diversity systems and crosstalk in multiplexing systems. These effects have been mostly neglected in the literature by applying far-field assumptions. Our results can thus be useful in the design of practical diversity or multiplexing FSO systems especially when a compact design is desired.
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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 | 0.003 | 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