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Record W2994730758 · doi:10.18280/ts.360508

Design and Analysis of Rectangular Microstrip Antenna (RMSA) for Millimeter Wave Communication Applications

2019· article· en· W2994730758 on OpenAlexvenueno aff
Umar Farooq, Ghulam Mohammad Rather

Bibliographic record

VenueTraitement du signal · 2019
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsExtremely high frequencyMicrostrip antennaAntenna (radio)AcousticsMicrostripComputer scienceTelecommunicationsElectronic engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

The millimeter wave (MMW) communication is a key technology for next-generation wireless applications.However, the antenna design remains a huge challenge for such applications at the MMW band.This paper designs a compact rectangular microstrip antenna (RMSA) for MMW applications at 33.5 GHz (Ka band) of the MMW spectrum.Simulation results show that the RMSA performed well and achieved the return loss of -16.33 dB, voltage standing wave ratio (VSWR) of 1.36, peak gain of 2.58dB and bandwidth of 0.76GHz.To improve the gain and other features, the RMSA was relied on to design an antenna array of 1×3 center feed and 1×3 end feed.The feasibility of the RMSA was verified through experiment and equivalent circuit analysis.The experimental and analysis results agree well with the simulation results.The research results provide supports to a wide range of applications in next-generation wireless networks.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.219
Teacher spread0.201 · 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
GenreMethods

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

Citations6
Published2019
Admission routes1
Has abstractyes

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