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Record W2019256558 · doi:10.1155/2011/675343

Impact of Vehicular Array Position on Urban MIMO Channel Characteristics

2011· article· en· W2019256558 on OpenAlexaff
Christopher C. Squires, T.J. Willink

Bibliographic record

VenueInternational Journal of Antennas and Propagation · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsMultipath propagationMIMOChannel (broadcasting)TransmitterAntenna arrayAntenna (radio)Vehicle-to-vehiclePosition (finance)Orientation (vector space)Antenna diversityDelay spreadComputer scienceElectronic engineeringTelecommunicationsEngineeringComputer network

Abstract

fetched live from OpenAlex

MIMO channel measurements have been performed in urban environments with antenna arrays positioned on the roof and sides of the measurement vehicle. Analysis of the data shows that the array's position on the vehicle, along with the location and orientation of the vehicle with respect to the transmitter, can have a considerable impact on the channel characteristics observed. Array elements on the vehicle's roof receive the same multipath components, and, therefore, have identically distributed channel responses. However, the characteristics of the multipath components observed at each side of the vehicle can differ significantly. Specifically, shadowing from the vehicle combined with the directionality of the side-mounted array elements affects the angular distribution and powers of the received multipath components, affecting the achievable diversity and channel capacity. This can have significant impact on system performance and should be considered when designing and analyzing vehicular-based signalling techniques.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score0.307

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 head0.236
Teacher spread0.223 · 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 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

Citations5
Published2011
Admission routes1
Has abstractyes

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