MétaCan
Menu
Back to cohort
Record W4293731774 · doi:10.1109/ojap.2022.3201627

A 5G Enabled Shared-Aperture, Dual-Band, in-Rim Antenna System for Wireless Handsets

2022· article· en· W4293731774 on OpenAlexafffund
Reza Shamsaee Malfajani, Farhad Bin Ashraf, Mohammad S. Sharawi

Bibliographic record

VenueIEEE Open Journal of Antennas and Propagation · 2022
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsPolytechnique Montréal
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsWirelessMulti-band deviceDual (grammatical number)Antenna (radio)Aperture (computer memory)TelecommunicationsComputer sciencePhysicsAcousticsArt

Abstract

fetched live from OpenAlex

In this work, we present a shared aperture (SA), dual-band in metal-rim antenna system targeting the sub-6GHz and millimeter-wave (mm-wave) bands of the 5G wireless standard. The antenna system consists of a SA cactus-shaped slot engraved on the side of standard mobile terminal rim that hosts a microwave radiating structure covering the sub-6 GHz bands as well as a 4-element slot based connected antenna array (SB-CAA) covering the mm-wave bands. This provides a compact sized solution for multiband operation within these bands. The CAA has beam forming capabilities where the beam can be steered between +/-30 degrees with acceptable gain and side lobe levels (SLL). A single 4-element slot based in-rim SB-CAA is also proposed that covered more than 6 GHz of frequency bandwidth (25.5–32 GHz) with a total efficiency exceeding 85% and realized averaged gain of 8.2 dBi over the bands covered. The SA cactus antenna structure had a bandwidth exceeding 3.5 GHz with total efficiency exceeding 75% and an average realized gain of 8 dBi between 26.5 – 30 GHz. For the microwave band covered (3.45-3.56 GHz) by this SA cactus antenna, a bandwidth of 140 MHz, efficiency of 90% with 2.5 dBi of measured gain were achieved.

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)0.001
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 score0.974
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.018
GPT teacher head0.235
Teacher spread0.217 · 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

Citations25
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueIEEE Open Journal of Antennas and PropagationSame topicAntenna Design and AnalysisFrench-language works237,207