Fade and Interfade Duration Characteristics in a Slant-Path <italic>Ka</italic>-Band Link
Bibliographic record
Abstract
Satellite-to-earth links are subject to several propagation effects in the troposphere, being rain attenuation the impairment that can cause the deepest fades. In this paper, the duration of both fades and the intervals between consecutive fades (interfade intervals) are characterized on the basis of the results of a long-term slant-path Ka-band propagation experiment carried out in Madrid, Spain. The experimental and statistical results included in this paper correspond to seven complete years of measurements, a period large enough to characterize not only the average-year statistics of fade dynamics but also their variability, which is assessed on the basis of annual statistics of durations. The obtained average-year statistics of fade durations are in many cases close to the predictions made by the International Telecommunication Union-Radiocommunications and Communications Research Center Canada models, although the predictions could be improved with a better selection of the parameters of the distributions used in the models. Interfade duration statistics are also presented and related to recent modeling efforts. The interannual variability of statistics, such as the relative number of fades, is quantified and found to be low, except for the higher attenuation thresholds or the highest durations considered in this paper.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| 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) | 0.001 | 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".