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Record W3152687023 · doi:10.1049/mia2.12116

Characterization of a 60 GHz scattered wireless channel with different antenna polarizations for underground multimedia applications

2021· article· en· W3152687023 on OpenAlexaff
Shah Ahsanuzzaman Md Tariq, Charles Despins, Sofiène Affes, Chahé Nerguizian

Bibliographic record

VenueIET Microwaves Antennas & Propagation · 2021
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsInstitut National de la Recherche ScientifiqueÉcole de Technologie SupérieureUniversité de MontréalUniversité du Québec à MontréalPolytechnique Montréal
Fundersnot available
KeywordsWirelessAntenna (radio)Channel (broadcasting)TelecommunicationsComputer scienceElectronic engineeringMultimediaElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract Large scale (i.e. <10 m) and small scale (i.e. 1 × 1× 1 cm) measurements and characterization of a scattered wireless channel with different antenna polarizations and configurations in the underground mine galleries at 60 GHz are addressed. Results show that the rough surface scattering and the gallery dimensions affect the path loss (PL) exponent and it becomes smaller than the free space. Vertically polarized antennas give a lower value of the PL exponent and root mean square (RMS) delay spread compared to the horizontal one. The small scale 3D measurement results show that the power loss of around 1–5 dB within a small scale cubical area. Results also show that the channel is less time dispersive in a wider gallery and observed a higher value of the RMS delay spread compared to a smaller gallery. The statistical results of the small scale multipath amplitude fading provide a better fit with the Rician distribution. The effects such as scattering, polarization, antenna radiation patterns, and waveguide which caused increase and decrease of the value of PL exponent and delay spread are also analysed. Results revealed that a directional narrow beam dual‐polarized antenna configuration might be a good candidate in this environment.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.011
GPT teacher head0.206
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2021
Admission routes1
Has abstractyes

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