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Record W1574624799 · doi:10.1109/wpmc.2002.1088174

Fading characteristics of RF signals due to foliage in frequency bands from 2 to 60 GHz

2003· article· en· W1574624799 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
TopicAntenna Design and Analysis
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsFadingRadio frequencyRadio spectrumAcousticsComputer scienceElectrical engineeringElectronic engineeringPhysicsTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

This paper compares the various temporal characteristics of radio channels for a broad range of frequencies, including 2.45, 5.25, 29 and 60 GHz, in various foliage and weather conditions. A substantial number of data points, in excess of 1.9 billions at 500 samples per second (equivalent to 45 days), was collected and analyzed for three particular types of channels: foliated deciduous trees, non foliated deciduous trees and coniferous trees. The radio channels are statistically analyzed and the resulting PDFs (probability density functions) and CDFs (cumulated density functions) are compared against existing models. Furthermore, wind speeds and rain precipitation are correlated with the power samples to consider RF propagation dependencies. Second order statistics are derived including level crossing rate (LCR) and average facie duration (AFD). The power profile is analyzed for spectral components. The frequency characteristics of the RF propagation channel are evaluated. Finally, channel-specific RF propagation attributes are presented.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score1.000

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 head0.012
GPT teacher head0.214
Teacher spread0.202 · 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

Quick stats

Citations54
Published2003
Admission routes1
Has abstractyes

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