MétaCan
Menu
Back to cohort
Record W1865776486 · doi:10.1109/ccece.2001.933733

Fade depth prediction on wireless microwave links using two-ray multipath model

2002· article· en· W1865776486 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTelecommunications and Broadcasting Technologies
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsFadeFadingMultipath propagationTerrainComputer sciencePath lossSatelliteRemote sensingElevation (ballistics)WirelessGeologyTelecommunicationsGeographyMathematicsEngineeringAerospace engineeringGeometryChannel (broadcasting)

Abstract

fetched live from OpenAlex

Fade depth prediction for airborne communication links is considered in this paper. There is no fading model for this specific scenario at the moment. The two closest models are the Olsen-Segal model for terrestrial links and the ITU-R model for satellite links. However, they cannot be directly applied to the airborne scenario. We propose a two-ray multipath fading model adapted to a realistic scenario of hilly or mountainous terrain, which applies to elevations angles higher than 2/spl deg/ and frequencies lower than 10 GHz, when the contribution of ground multipath component is dominant. It is interesting to note that the two-ray model predicts roughly the same fade depth dependence on the path clearance angle as the Olsen-Segal model, which may be considered as a theoretical justification, as to the best of our knowledge- for the first time, of the path elevation angle factor in that model. We further propose a hybrid approach to account for the atmospheric contribution to the total fade depth.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score0.499

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)0.0000.000

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 head0.056
GPT teacher head0.246
Teacher spread0.190 · 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