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Record W3017241019 · doi:10.1109/tap.2020.3030972

Millimeter-Wave Huygens’ Transmit Arrays Based on Coupled Metallic Resonators

2020· article· en· W3017241019 on OpenAlexaff
S. Sakurai, João G. Nizer Rahmeier, Takashi Tomura, Jiro Hirokawa, Shulabh Gupta

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2020
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsCarleton University
FundersSupport Center for Advanced Telecommunications Technology Research Foundation
KeywordsOpticsPhysicsResonatorNear and far fieldCircular polarizationDielectric resonatorPrinted circuit boardBandwidth (computing)WavefrontAcousticsTelecommunicationsElectrical engineeringComputer scienceMicrostripEngineering

Abstract

fetched live from OpenAlex

A novel Huygens' transmit array (TA) is proposed based on a coupled-resonator approach to demonstrate millimeter-wave (mm-Wave) beamforming for linear polarization. The proposed structure is simple and compatible with standard printed circuit board (PCB) processes and utilizes a single dielectric substrate only. It is shown that by engineering the geometrical dimensions of the resonator, its electric (even-mode) and magnetic (odd-mode) resonances are excited in a balanced manner to achieve zero backscattering in a large bandwidth. This operation principle of the proposed Huygens' cell is explained in detail using both an insightful equivalent circuit model, as well as full-wave eigenmode analysis. Next, the proposed Huygens' cell is placed on top of a high-gain 2-D slot-array antenna, in its near field, to engineer its aperture field distribution. Several TA prototypes designed around the 60 GHz frequency band are demonstrated and experimentally characterized in both their near and far fields, to achieve difference pattern generation, beam expansion, and beam steering as application examples, in addition to a uniform surface demonstrating its low-loss performance.

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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 communication0.0010.000
Open science0.0010.000
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 head0.026
GPT teacher head0.206
Teacher spread0.181 · 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

Citations40
Published2020
Admission routes1
Has abstractyes

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