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Ridge Gap Waveguide Wideband Hybrid Directional Coupler for Ka-Band Applications

2020· article· en· W3032112129 on OpenAlexaff
Mohamed Yasser Soliman, Mohamed Mamdouh M. Ali, Shoukry I. Shams, Mohamed Fathy Abo Sree, Diaa E. Fawzy, A. M. M. A. Allam

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsConcordia University
Fundersnot available
KeywordsHybrid couplerWidebandPower dividers and directional couplersBandwidth (computing)Computer scienceWirelessElectronic engineeringMicrowaveFrequency bandElectrical engineeringTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

The fifth generation (5G) is the next wireless mobile communication technology that targets to provide huge capac-ity, low latency and high data speeds. Like any new wireless technology, 5G requires the development of exciting techniques, where access to high frequency spectrum can achieve the desired characteristics. In addition, new systems must be developed and designed using wide bandwidth microwave components, which should be implemented with modern and efficient guiding structures. Among all the microwave components, directional coupler is essential device as it can be used to realize many subsystems such as beamforming networks. In order to keep up with the huge changes in future technologies, couplers still requires noticeable improvement, where wide bandwidth and low loss should be achieved throughout using modern guiding technology such as Ridge Gap Waveguide (RGW). In this paper, a design of ultra-wideband 3 dB quadrature hybrid directional coupler using RGW technology is introduced. The proposed coupler has a compact size of 1.58 λ×1.4λ and achieves a relative bandwidth of 44.7% at 33.5 GHz, which cover the whole ka-band. In addition, a stable 90° phase difference between the coupling and transmission coefficients is obtained over the whole frequency band.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.021
GPT teacher head0.222
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2020
Admission routes1
Has abstractyes

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