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Metasurface Superstrate for 5G Bandwidth and Gain Enhancement

2022· article· en· W4296908688 on OpenAlexaff
Asif Bilal, Abdul Quddious, Haris Votsi, Atsushi Kanno, Tetsuya Kawanishi, Marco A. Antoniades, Stavros Iezekiel

Bibliographic record

Venue2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (AP-S/URSI) · 2022
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsToronto Metropolitan University
FundersEuropean Regional Development Fund
KeywordsBandwidth (computing)MetamaterialAntenna gainSplit-ring resonatorResonatorMulti-band deviceHigh-gain antennaOptoelectronicsMetamaterial antennaMicrostrip antennaPatch antennaMaterials scienceOpticsPhysicsElectronic engineeringAntenna (radio)Computer scienceElectrical engineeringEngineeringAntenna efficiencyAntenna factorTelecommunications

Abstract

fetched live from OpenAlex

This paper discusses a dual-layer metasurface (MSF) superstrate, consisting of double split-ring resonator cells in the 28 GHz 5G mm-wave frequency band. The MSF superstrate is added above a conventional patch antenna, and an enhancement in the performance of the patch antenna in terms of bandwidth and gain is achieved. This is due to the negative index metamaterial (NIM) properties of the designed MSF superstrate. In this design, the impedance bandwidth is improved from 2.6 GHz to 3.6 GHz, while the gain of the patch antenna is increased from 6.59 dBi to 12.9 dBi. The simplicity of the design to achieve a higher gain and broader bandwidth makes it a suitable candidate for applications in 5G mm-wave communications.

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)0.002
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 score0.946
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.016
GPT teacher head0.247
Teacher spread0.231 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

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