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Record W2112673589 · doi:10.1109/ccece.2009.5090206

Simulation of rain fading and scintillation on Ka-band Earth-LEO satellite links

2009· article· en· W2112673589 on OpenAlexaff
David G. Michelson, Weiwen Liu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPrecipitation Measurement and Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFadingGeostationary orbitScintillationSatelliteFadeCommunications satelliteKa bandMeteorologyAtmosphere (unit)Remote sensingKu bandEnvironmental scienceComputer scienceGeologyPhysicsTelecommunicationsChannel (broadcasting)Astronomy

Abstract

fetched live from OpenAlex

In the near future, many of the research, communications relay and Earth observation satellites that will be placed into low Earth orbit (LEO) will use high speed Ka-band links to communicate with Earth stations during the short time they pass over a given location. The motion of a LEO satellite across the sky will cause the Earth-space path to pass through any rain cells and turbulence cells in the vicinity very quickly leading to steeper fade slopes and more rapid scintillation than in the well-studied geostationary case. Until extensive measurement programs are undertaken, simulation based upon reasonable models of the atmosphere is the likely best option for assessing the severity of fading on such links. If the spatial statistics and/or distributions of the rain and turbulence cells are known, one can predict the rate at which rain fading and scintillation will occur. We have used this insight to construct a channel simulator that can provide plausible predictions of the instantaneous path loss on Earth-LEO links during a given pass.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.433
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.030
GPT teacher head0.246
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2009
Admission routes1
Has abstractyes

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