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Record W2999247874 · doi:10.1049/iet-map.2019.0591

Twenty‐eight‐gigahertz beam‐switching ridge gap dielectric resonator antenna based on FSS for 5G applications

2020· article· en· W2999247874 on OpenAlexaff
Mehri Borhani Kakhki, Abdolmehdi Dadgarpour, Abdel‐Razik Sebak, Tayeb A. Denidni

Bibliographic record

VenueIET Microwaves Antennas & Propagation · 2020
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsConcordia UniversityInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsDielectric resonatorDielectric resonator antennaResonatorRidgeAntenna (radio)Materials scienceDielectricOptoelectronicsOpticsBeam (structure)Electrical engineeringPhysicsEngineeringGeology

Abstract

fetched live from OpenAlex

A new design of the double dielectric resonator antenna (DRA) fed by a printed ridge gap waveguide for beam‐switching applications based on frequency selective surfaces (FSSs) is presented here. The dual‐sided printed FSS element works in its reflection mode and comprises a slotted square C‐shaped patch on the top layer and a square strip on the back plane. Therefore, the beam switching can be implemented by loading the proposed FSS array over and in the middle of DRAs. Loading the antenna with two layers of 3 × 3 FSS unit cells results in ±77° beam switching and a 3.16 dBi gain enhancement at 28 GHz. Simulation and measurements confirm the operation of the proposed antenna, with good matching and gain observed.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.978
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
Bibliometrics0.0000.001
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 head0.018
GPT teacher head0.224
Teacher spread0.206 · 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 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

Citations17
Published2020
Admission routes1
Has abstractyes

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