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Record W4403497673 · doi:10.1002/mop.34344

Gain enhancement of compact CPW‐Fed ultra‐wideband antenna using an FSS reflector

2024· article· en· W4403497673 on OpenAlexaff
Boualem Hammache, Idris Messaoudene, Massinissa Belazzoug, Salem Titouni, Abderraouf Messai, Tayeb A. Denidni

Bibliographic record

VenueMicrowave and Optical Technology Letters · 2024
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsWidebandReflector (photography)Ultra-widebandAntenna (radio)High-gain antennaOptoelectronicsOpticsMaterials scienceElectrical engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

Abstract In this paper, an enhancement gain of compact CPW‐Fed antenna using a single layer frequency selective surfaces (FSSs) reflector for ultra‐wideband (UWB) applications is presented. A hexagonal CPW‐Fed antenna with a size of 30 × 30 mm 2 is realized to provide a UWB bandwidth operation. In this study, a novel design of an FSS unit cell with reduction and a small size of 8 × 8 mm 2 is proposed. It allows one to achieve a UWB band‐stop response between 3 and 11.5 GHz. The FSS reflector has 7 × 7 units with a total size of 56 × 56 mm 2 . This reflector is placed below the antenna at a distance of 20 mm. The main objective of this contribution is to improve the gain level of the antenna, where the proposed antenna achieves an improvement of realized gain of 6.2 dBi with increasing from 2.2 to 8.4 dBi. The antenna became more directive after the integration of the FSS reflector with a directional radiation pattern. The numerical and experimental results are in good concordance with the simulated one. This study is performed in terms of voltage standing wave ratio, radiation pattern, realized gain, and radiation efficiency.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.334
Threshold uncertainty score0.641

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 head0.018
GPT teacher head0.252
Teacher spread0.234 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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