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Record W2108999157

A reconfigurable chassis-mode MIMO antenna

2013· article· en· W2108999157 on OpenAlexaff
Krishna Kumar Kishor, Sean V. Hum

Bibliographic record

VenueEuropean Conference on Antennas and Propagation · 2013
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsReconfigurable antennaMIMO3G MIMOAntenna (radio)Electronic engineeringComputer scienceRadiation patternOmnidirectional antennaAntenna measurementAntenna efficiencyPIN diodeEngineeringTelecommunicationsElectrical engineeringDiode
DOInot available

Abstract

fetched live from OpenAlex

Reconfigurable MIMO antennas have the potential to improve the performance of a MIMO antenna system operating in a changing environment. This paper presents a novel reconfigurable MIMO antenna that utilizes pattern diversity to provide increased adaptability via reconfiguring the radiation pattern. It is designed using the characteristic modes of the structure which are manipulated using two tunable parasitic elements. Simulation studies of this two-port antenna confirm that the radiation patterns are orthogonal to each other in each of the two states of the antenna, as well as between the two states, thus indicating its use as a potential reconfigurable MIMO antenna. Measured two-port S-parameters of a prototype employing switched PIN diode loading correspond well with simulations.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score1.000

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)0.0010.001

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 head0.023
GPT teacher head0.218
Teacher spread0.194 · 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.

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

Citations3
Published2013
Admission routes1
Has abstractyes

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