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Record W2748784711 · doi:10.1109/lawp.2017.2742862

High-Gain Wideband Partially Reflecting Surface Antenna for 60 GHz Systems

2017· article· en· W2748784711 on OpenAlexaff
Djamel Abbou, Tan-Phu Vuong, R. Touhami, Fabien Ferrero, D. Hamzaoui, M.C.E. Yagoub

Bibliographic record

VenueIEEE Antennas and Wireless Propagation Letters · 2017
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsWidebandAntenna gainBandwidth (computing)Microstrip antennaAntenna measurementBroadsideHigh-gain antennaElectrical engineeringElectronic engineeringAntenna factorAntenna (radio)EngineeringOpticsPhysicsTelecommunications

Abstract

fetched live from OpenAlex

In this letter, a high-gain wideband antenna for 60 GHz wireless personal area networks is proposed. It consists of an inset-fed microstrip antenna with a partially reflecting surface (PRS) acting as a Fabry-Perot cavity. Good agreement was achieved between simulated and measured data, showing a wide bandwidth, covering two channels of the 60 GHz band and a maximum experimental gain of 16.4 dBi in the broadside direction at 60 GHz. The proposed structure meets the IEEE 802.15.3c standard requirements in terms of gain and bandwidth while the novel shape of the PRS array makes it smaller compared to existing 60 GHz Fabry-Perot antennas. Moreover, a low-cost printed circuit board technology is used to manufacture antenna prototype.

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 score0.003

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 head0.025
GPT teacher head0.253
Teacher spread0.229 · 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

Citations37
Published2017
Admission routes1
Has abstractyes

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