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Record W1508202077 · doi:10.1109/iccw.2015.7247344

3-Dimensional Large-Scale Channel Model for Urban Environments in mmWave Frequency

2015· article· en· W1508202077 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMillimeter-Wave Propagation and Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsFadingPath lossTransmitterShadow mappingChannel (broadcasting)Computer scienceDelay spreadRay tracing (physics)Log-distance path loss modelStandard deviationShadow (psychology)Topology (electrical circuits)TelecommunicationsMathematicsStatisticsElectrical engineeringPhysicsEngineeringOpticsWirelessArtificial intelligence

Abstract

fetched live from OpenAlex

From the results of the ray-tracing simulation of 28 GHz frequency band over downtown of Ottawa and New York University campus, we propose 3D large-scale channel models for urban city which are applicable to a mmWave version of 3D spatial channel model. Due to the change of geographical topology dimension from 2D to 3D, the height information of the transmitter should be reflected to the parameters of the channel model such as line-of-sight probability, Ricean K factor, path loss and shadow fading accordingly. In the simulation results, the line-of-sight probability depends on the height of the transmitter compared to the 2D model. The dual-slope path loss model is still appropriate in 3D channel model. We also propose the linear standard deviation function of the shadow fading, which shows a large standard deviation and an increasing trend with the distance.

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.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.884
Threshold uncertainty score0.440

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 head0.040
GPT teacher head0.228
Teacher spread0.188 · 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

Quick stats

Citations15
Published2015
Admission routes1
Has abstractyes

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