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Record W4293370940 · doi:10.1109/access.2022.3201865

Ultra-Wideband Compact Millimeter-Wave Printed Ridge Gap Waveguide Directional Couplers for 5G Applications

2022· article· en· W4293370940 on OpenAlexaff
Mohamed Mamdouh M. Ali, Osama M. Haraz, Islam Afifi, Abdel-Razik Sebak, Tayeb A. Denidni

Bibliographic record

VenueIEEE Access · 2022
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsInstitut National de la Recherche ScientifiqueConcordia University
Fundersnot available
KeywordsWidebandBandwidth (computing)Extremely high frequencyPower dividers and directional couplersHybrid couplerOpticsAmplitudeMaterials scienceMillimeterOptoelectronicsPhysicsComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

A compact ultra-wideband printed ridge gap waveguide directional couplers for millimeter-wave applications are presented in this paper. A multi-layer coupling technique between two resonant patches is adopted to achieve a wider operating bandwidth with better amplitude and phase balance compared to single-layer technology. For this purpose, a systematic design procedure is deployed to achieve several coupling values in the range of 3-10 dB over a wide frequency bandwidth centered at 30 GHz. A 3-dB hybrid coupler is fabricated and measured, where a bandwidth of 12 GHz (about 38 % fractional bandwidth) from 25 GHz to 37 GHz is achieved. In addition, the phase balance is 90° ± 5° over 38% fractional bandwidth with an amplitude balance of 3.4 ± 0.5 dB over a 26.5% centered at 30 GHz. The proposed couplers with superior characteristics such as compactness, low loss, and low dispersion are considered a good candidate for millimeter-wave applications such as the fifth-generation (5G) wireless communications.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.888
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)0.0000.000

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 head0.044
GPT teacher head0.274
Teacher spread0.230 · 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

Citations20
Published2022
Admission routes1
Has abstractyes

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