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Record W2937752222 · doi:10.1049/iet-map.2018.5768

Design and analysis of a millimetre‐wave high gain antenna

2019· article· en· W2937752222 on OpenAlexaff
Elham Erfani, Safieddin Safavi‐Naeini, Serioja Ovidiu Tatu

Bibliographic record

VenueIET Microwaves Antennas & Propagation · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsUniversity of WaterlooInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsMillimetre waveHigh-gain antennaAntenna (radio)Antenna gainMillimeterExtremely high frequencyElectronic engineeringComputer scienceTelecommunicationsElectrical engineeringEngineeringAntenna measurementPhysicsOpticsAntenna factor

Abstract

fetched live from OpenAlex

A broadband and high gain transmit array (TA) antenna, operating at 60 GHz, is proposed. To meet the design requirements of a TA antenna with polarisation‐insensitive radiation performance, an optimal multi‐layer unit cell (UC) is introduced. The dimensions of the UC are parametrically expressed to realise a linear transmission phase response with a variation range of 270° and insertion loss <−3 dB over the desired frequency band ranging from 58 to 64 GHz. A new planar array composed of 2 × 4 aperture‐coupled‐patches interleaved with a soft‐surface is also designed as a feed for the proposed TA. Furthermore, a hybrid method based on full‐wave simulations and analytical formulations is developed to calculate the radiation characteristics of the TA antenna and the results are compared to the ones achieved with full‐wave simulations. The designed TA antenna is fabricated and the measurement results are presented. The obtained results show peak aperture efficiencies of 38.48% (30.85 dB peak gain) and 32.37% (30.1 dB peak gain), and −1 dB gain bandwidths of 7.7 and 8.2% from the full‐wave simulations and measurements, respectively. Such a broadband and high gain antenna is deemed to be suitable for mm‐wave backhaul links in 5G cellular systems.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.835

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.013
GPT teacher head0.211
Teacher spread0.198 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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