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Wideband Millimeter Wave Planner Sub-array with Enhanced Gain for 5G Communication Systems

2020· article· en· W3126544815 on OpenAlexaff
Yuanzhi Liu, M.C.E. Yagoub

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsWidebandBandwidth (computing)Extremely high frequencySplitterDipole antennaHigh-gain antennaArray gainAntenna arrayAntenna gainReflective array antennaComputer scienceElectronic engineeringCollinear antenna arrayPhysicsElectrical engineeringAntenna (radio)EngineeringOpticsTelecommunicationsAntenna efficiencySlot antenna

Abstract

fetched live from OpenAlex

A compact wideband millimeter wave planner sub-array with enhanced gain is presented in this paper. Aimed at supporting 5G communication systems, it Consists of a loop patch, which serves simultaneously as power splitter and radiation part, and two dipole patches. The proposed 2D antenna element exhibits a high gain of 6.8 dBi at 28 GHz and a wide impedance bandwidth of 25.8 - 37.8 GHz with |S11| <; -10 dB. Next, its designed planner sub-array has a gain of 12.5 dBi and a -10 dB fractional bandwidth of 34.3%. The sub-array has a compact size of 26 mm × 26.5 mm and can be used as a module to form large 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 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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.017
GPT teacher head0.193
Teacher spread0.176 · 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 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

Citations4
Published2020
Admission routes1
Has abstractyes

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