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Record W2996951069 · doi:10.1109/lawp.2019.2961641

Deterministic Modeling of Indoor Stairwells Propagation Channel

2019· article· en· W2996951069 on OpenAlexafffund
Vincent Fono, Larbi Talbi, Ousama Abu Safia, Mourad Nedil, Khelifa Hettak

Bibliographic record

VenueIEEE Antennas and Wireless Propagation Letters · 2019
Typearticle
Languageen
FieldEngineering
TopicMillimeter-Wave Propagation and Modeling
Canadian institutionsUniversité du Québec en Abitibi-TémiscamingueCommunications Research Centre CanadaCarleton UniversityUniversité du Québec en Outaouais
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChannel (broadcasting)Computer scienceElectronic engineeringAcousticsTelecommunicationsPhysicsEngineering

Abstract

fetched live from OpenAlex

A deterministic approach is presented for modeling a wireless propagation channel in a stairwell environment. The ray-tracing method is used to find the reflected and diffracted rays with the highest contribution to the total received power at a given location. Most significant reflected rays occur at the surfaces of specific steps of the stairwell and the surrounding lateral walls, while most significant diffracted beams emanate from the edges of steps located between transmitter and receiver antennas. The uniform theory of diffraction is used to calculate the diffracted contributions from the edges, whereas the multiple diffractions are calculated using heuristic diffraction coefficients. Unlike the reported models, the proposed model is deterministic and focuses on the radio propagation within stairwells at the X-band frequencies range. Experimental validation is performed using two types of antennas, horns and patches, for an operating frequency of 10 GHz. Simulated results of narrowband and wideband radio channels showed a good agreement with the experimental ones. The correlation coefficient between measured and simulation results is around 80% on average, and the residual errors between measured and simulated total received power results are less than 13%, which means that the proposed model has fair accuracy for such complex environments.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.752
Threshold uncertainty score0.893

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 head0.013
GPT teacher head0.205
Teacher spread0.192 · 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 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

Citations6
Published2019
Admission routes2
Has abstractyes

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