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A New Approach to Modeling Indoor Wireless Communications Channel at EHF

2005· article· en· W24779488 on OpenAlexaff
Yongming Huang, Tayeb A. Denidni, Larbi Talbi, Kamel Adi

Bibliographic record

VenuePhysiotherapy Theory and Practice · 2005
Typearticle
Languageen
FieldEngineering
TopicMillimeter-Wave Propagation and Modeling
Canadian institutionsUniversité du QuébecUniversité du Québec en Outaouais
Fundersnot available
KeywordsMultipath propagationTransmitterRay tracing (physics)Channel (broadcasting)Computer scienceWirelessSide lobeAntenna (radio)FadingElectronic engineeringExtremely high frequencyCommunications systemTelecommunicationsEngineeringOpticsPhysics

Abstract

fetched live from OpenAlex

In indoor wireless communications systems, the antenna radiation patterns at the transmitter and the receiver have a significant influence on the channel characteristics. The work reported in this paper give insight about a new approach for modeling the effects of the radiation patterns of the directional horn antenna. The propagation modeling of the indoor multipath channel is based on the ray tracing technique. The main lobe and side lobes are dealt separately in the new model. More accurate details are obtained, in terms of fading variations. In order to validate the proposed model, continuous wave (CW) experimental measurements are conducted for indoor radio channels at 37.2 GHz within a typical empty room and fitted well with the simulation results. It will be helpful in establishing design guidelines for point-to-point indoor communications systems using millimeter waves.

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: none
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.043
GPT teacher head0.313
Teacher spread0.269 · 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
Published2005
Admission routes1
Has abstractyes

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