MétaCan
Menu
Back to cohort
Record W2086773722 · doi:10.1109/aps.2012.6348878

Experimental characterization of the Underground UWB channel

2012· article· en· W2086773722 on OpenAlexaff
M. Moutairou, G.Y. Delisle, N. Kandil

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsBandwidth (computing)WidebandParametric statisticsFrequency responseChannel (broadcasting)Mean squared errorCenter frequencyFrequency domainRange (aeronautics)Parametric modelDelay spreadCharacterization (materials science)Frequency bandFrequency dependenceUltra-widebandComputer scienceAcousticsElectronic engineeringTelecommunicationsMathematicsStatisticsEngineeringPhysicsElectrical engineeringOpticsFading

Abstract

fetched live from OpenAlex

Results from parametric modeling of the indoor channel frequency response for very large number of sweeps over a frequency range of 3 GHz to 10 GHz are presented. The characterization of the frequency-dependence of the ultra wideband mining channel across the considered bandwidth is addressed and the smooth frequency response is evaluated using an Auto Regression (AR) method, which is proved in this study, sufficient to better approximate each recorded frequency response. This study concludes that the number of poles needed to describe the AR process is always less than 2 in the studied area. The appropriated poles of the model are obtained by minimizing the root means squared error (RMSE) between the original frequency response measurement and the predicted one. It is finally found out that the frequency decaying factor (δ) is around 0.5 in the underground area on study.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.130

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 head0.012
GPT teacher head0.209
Teacher spread0.197 · 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 designBench or experimental
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

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same topicUltra-Wideband Communications TechnologyFrench-language works237,207