Air-to-Ground Large-Scale Channel Characterization by Ray Tracing
Why this work is in the frame
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Bibliographic record
Abstract
Through ray tracing simulation on three-dimensional (3D) urban environments, we characterize air-to-ground (A2G) channels for 5G and beyond wireless communications. In this study, we review four types of elevation angle-dependent probability of line-of-sight (LoS) expressions according to building distribution types. With channel characterization data extracted from the ray tracing (RT) simulation, LoS probability versus elevation angle agrees better with the elevation angle-dependent probability expressions of LoS that assumes the buildings are randomly distributed. Furthermore, we provide a more accurate LoS probability expression that enables better curve-fitting for the LoS probability data obtained from RT simulations. In addition, the A2G channel parameters such as LoS and non-line-of-sight (NLoS) channel path loss exponents (PLEs) and the shadow fading with UAV altitudes are obtained in four typical and realistic urban environments. The LoS PLEs increase slowly with the height of the UAV, while the NLoS one decreases significantly with the increase of the UAV height.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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