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Record W2981035485 · doi:10.1109/access.2019.2947481

Cross-Configuration Substrate Integrated Waveguide Beamforming Network for 1D and 2D Beam Patterns

2019· article· en· W2981035485 on OpenAlexafffund
Chad Bartlett, Jens Børnemann

Bibliographic record

VenueIEEE Access · 2019
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Waterloo
KeywordsBeamformingWaveguideSubstrate (aquarium)Materials scienceBeam (structure)OptoelectronicsComputer scienceOpticsTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

This paper presents the simulated and measured results of a dual-layer substrate integrated waveguide (SIW) beamforming network utilizing an 8 × 8 cross-configuration Butler matrix over a frequency range of 28.5 to 31.5 GHz. By arranging the input ports on the bottom SIW layer and employing dual-layer passband filters as a detachment point, the top SIW layer can be interchanged with the purpose of exploring one-dimensional and two-dimensional broadside beam patterns. Although Butler matrices are not typically utilized for beamforming in this configuration, two examples of interchangeable top layer arrays are demonstrated; the first being a 2 × 8 slot antenna array for 1-D scanning, and the second being a 2 × 4 center-slot array for 2-D scanning. Each of the beamforming network's simulated and measured 10 dB bandwidth is demonstrated over a range of 28.5 to 31.5 GHz. Additional design details and dimensions are specified for the aforementioned passband filter transitions, as well as for each of the slot antenna arrays.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score0.885

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 head0.015
GPT teacher head0.261
Teacher spread0.246 · 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

Citations10
Published2019
Admission routes2
Has abstractyes

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