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Record W2159801046 · doi:10.1109/tvt.2008.2004494

An Analysis of Probability Distribution of Doppler Shift in Three-Dimensional Mobile Radio Environments

2008· article· en· W2159801046 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

VenueIEEE Transactions on Vehicular Technology · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsBlackberry (Canada)
Fundersnot available
KeywordsProbability density functionDoppler effectAutocorrelationSpectral densityMathematicsMathematical analysisProbability distributionSIGNAL (programming language)StatisticCharacteristic function (probability theory)StatisticsAcousticsStatistical physicsPhysicsComputer science

Abstract

fetched live from OpenAlex

The Doppler shift (DS) distribution of the signal that is received by a mobile station in 3D mobile radio environments is closely related to the signal's power spectral density (PSD). From the relationship between the arriving angles and the DS, general equations are derived, bridging the probability density function (pdf) of the elevation angle with the pdf of the DS, its variance, and the characteristic function. These equations are then used to analyze the statistic distribution of the DS based on the semispheroid model, which has been recently proposed by Janaswamy. For this particular model, analytical expressions for the pdf and the variance of the DS have been derived, and a definite-integral expression is provided for the characteristic function. When the average strengths of the waves that are distributed on different equal-Doppler-shift surfaces are assumed to be equal, the derived pdf of the DS is equivalent to the signal's PSD, and the derived characteristic function of the DS is equivalent to the signal's autocorrelation function.

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: none
Teacher disagreement score0.498
Threshold uncertainty score0.598

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.007
GPT teacher head0.208
Teacher spread0.200 · 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