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Level of detail of the physical environment and its impact on propagation prediction for a 60-GHz fixed radio link

2021· article· en· W3160777945 on OpenAlexaffabout
C. Amaya, Marcel A. LeClair, Vincent Picard, Reza Chaharmir, Ming Li, Simon Perras

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMillimeter-Wave Propagation and Modeling
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsTransmitterDowntownCanyonMultipath propagationStreet canyonRay tracing (physics)Radio propagationLink (geometry)Computer scienceRadio Link ProtocolTelecommunicationsElectrical engineeringEngineeringWirelessGeographyComputer networkPhysicsChannel (broadcasting)OpticsCartography

Abstract

fetched live from OpenAlex

3D models that capture the characteristics of a physical environment in downtown Ottawa with three different levels of detail (LOD) have been developed. This paper investigates the impact of using different LODs of a downtown street canyon on multipath power predicted by ray tracing on a 60-GHz fixed radio link. The 60-GHz radios are equipped with high-gain directional antennas placed at street level below building rooftops. Results are produced and analyzed for two link configurations: with the transmitter and receiver placed on the same sidewalk of the street canyon and, with transmitter and receiver placed on opposite sidewalks.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.061
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
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 head0.047
GPT teacher head0.248
Teacher spread0.201 · 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 designSimulation or modeling
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

Citations1
Published2021
Admission routes2
Has abstractyes

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