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Record W3126499278 · doi:10.1049/mia2.12110

Collocated MIMO travelling wave SIW slot array antennas for millimetre waves

2021· article· en· W3126499278 on OpenAlexafffund
Asim Ghalib, Mohammad S. Sharawi, R. Mittra, Hussein Attia, Atif Shammim

Bibliographic record

VenueIET Microwaves Antennas & Propagation · 2021
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsPolytechnique Montréal
FundersKing Abdullah University of Science and TechnologyKing Fahd University of Petroleum and MineralsPolytechnique Montréal
KeywordsMIMOBandwidth (computing)Extremely high frequencyMillimetre waveAntenna arrayAntenna (radio)MillimeterElectronic engineeringPhysicsAcousticsComputer scienceEngineeringTelecommunicationsOpticsBeamforming

Abstract

fetched live from OpenAlex

Abstract A novel four‐element collocated travelling wave substrate integrated waveguide (SIW) multiple‐input multiple‐output (MIMO) antenna covering millimetre wave (mm‐wave) bands (28–32 GHz) is presented. The antenna exhibits a matching bandwidth of more than 4 GHz and a measured gain of 15 dBi. The MIMO antenna elements are collocated, thus significantly reducing the size of the proposed design. To spatially isolate the beams (obtain lower correlation coefficient) of the MIMO antenna elements, the beams are oriented in different directions. The slots within each SIW array are designed to provide tilted beams, thus eliminating the need for a beam switching network. Four distinct beams are formed towards ±10 ° and ±30 ° . The dimension of the four‐element MIMO SIW design is 68 × 30.68 × 0.5 mm 3 . The proposed antenna has a high gain, compact size, simpler feeding and enhanced MIMO capability compared to other SIW antennas proposed in the literature.

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)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.017
GPT teacher head0.216
Teacher spread0.199 · 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

Citations5
Published2021
Admission routes2
Has abstractyes

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