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Record W4388240402 · doi:10.1109/access.2023.3329750

Millimeter-Wave ME-Dipole Array Antenna Decoupling Using a Novel Metasurface Structure

2023· article· en· W4388240402 on OpenAlexaff
Oludayo Sokunbi, Ahmed A. Kishk

Bibliographic record

VenueIEEE Access · 2023
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsConcordia University
Fundersnot available
KeywordsOpticsRadiation patternDipole antennaPhysicsMetamaterialBandwidth (computing)Extremely high frequencySplit-ring resonatorMaterials scienceOptoelectronicsAntenna (radio)Computer scienceTelecommunications

Abstract

fetched live from OpenAlex

A novel customized π-shaped split-ring resonator metasurface arranged in two configurations is presented to decouple 1×2 and 1×4 Millimeter-Wave (MMW) Magneto-Electric (ME) Dipole in the H-Plane with 1.6 mm (0.32λ at 60 GHz) inter-element spacing. The metamaterial unit cell is first designed to inhibit the propagation of coupled surface waves within the bandwidth of interest. A 5×2 arrangement of this unit cell is carefully positioned on the top and bottom of the superstrate with 1 mm spacing (0.2λ at 60 GHz) between the antenna and the superstrate. In the 1×2 array, a maximum measured mutual coupling reduction of 53 dB is observed within the 52-66 GHz bandwidth (23.7%). To further demonstrate the uniqueness of the metasurface, an 11×2 configuration of this unit cell is arranged as a superstrate for the 1×4 ME-dipoles. A maximum measured mutual coupling reduction of 40 dB is achieved without a considerable effect on the radiation characteristics. Parametric analysis is performed to confirm the uniqueness of this new decoupling structure. The proposed antenna exhibits measured high total efficiency (> 89%), high gain (> 8 dB), low envelope correlation coefficient (<0.0003), and very good radiation characteristics throughout the entire bandwidth. The fabricated prototype antenna is measured to validate the simulation results. The proposed antenna is a good recommendation for V-band millimeter-wave MIMO applications like radar research.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.850
Threshold uncertainty score0.980

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 head0.069
GPT teacher head0.288
Teacher spread0.219 · 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 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

Citations8
Published2023
Admission routes1
Has abstractyes

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