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Record W3136297882 · doi:10.18280/i2m.200101

60 GHz Broadband LTCC Antenna for 5G Mobile Communication Systems

2021· article· en· W3136297882 on OpenAlexaffvenue
Djamel Khezzar, Djamel Khedrouche, Tayeb A. Denidni

Bibliographic record

VenueInstrumentation Mesure Métrologie · 2021
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsHFSSBroadbandBandwidth (computing)Microstrip antennaElectronic engineeringMaterials scienceWidebandTransmitterWirelessElectrical engineeringAntenna (radio)OptoelectronicsEngineeringTelecommunicationsChannel (broadcasting)

Abstract

fetched live from OpenAlex

This paper provides a numerical investigation in designing wideband circularly polarized 60 GHz antenna using Low-Temperature Co-fired Ceramic technology (LTCC). The LTCC provides high-density multilayer integration, low dielectric loss, and low costs. The use of LTCC technology is advantageous for easy and flexible 3D integration and freer vias distribution in the substrate. The designed antenna focuses on obtaining a better trade-off in terms of size, gain, circular polarization (CP), and large bandwidth. The circular polarization was chosen in order to minimize the transmission errors caused by polarization inconsistency between the transmitter and the receiver. The antenna geometry is developed taking into consideration the design rules of the LTCC with a layer thickness of 100 µm after firing and a metal layer thickness of 9 µm. A bandwidth of more than 33% centered at 60 GHz was obtained for this designed multilayer antenna. The results are obtained by using the High-Frequency Structure Simulator (HFSS). The proposed integrated antenna can be used in future 5G wireless communication systems and other 60 GHz spectrum applications.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.260
Teacher spread0.241 · 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 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

Citations1
Published2021
Admission routes2
Has abstractyes

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