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Record W4288052526 · doi:10.21203/rs.3.rs-1878891/v1

Circularly Polarized Printed MIMO Antenna for 5G Applications

2022· preprint· en· W4288052526 on OpenAlexaboutno aff
Acharya Gangula, Rama Krishna Challa, Nandini gaddam, Rihana Begum Karji

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMIMOGround planeTurnstile antennaPatch antennaPhysicsOpticsMonopole antennaCoaxial antennaMicrostrip antennaAntenna factorElectronic engineeringTelecommunicationsComputer scienceAntenna (radio)Engineering

Abstract

fetched live from OpenAlex

Abstract This study provides a proposal for printed circularly polarized MIMO 5G antenna with four ports that are suitable for enhanced impedance bandwidth. The proposed circularly polarized MIMO antenna is designed at 28 GHz. The complementary split ring rectangular resonator with a defective ground plane is used to support the array, which is placed on a FR4 epoxy substrate that is 40 mm × 40 mm × 0.8 mm in physical size. The MIMO 5G antenna components are structured in an orthogonal arrangement with four identical patches that have a triangular cut. By integrating triangular cuts on rectangular patch and inset feeding techniques, the the designed antenna work across the whole frequency range with good impedance matching, increased gain, and with 1.5 GHz axial ratio bandwidth for circular polarization. The circular polarized MIMO 5G antenna that has been proposed achieves a gain of 5 dBi over bandwidth of 7GHz. The circularly polarized MIMO antenna would cover 5G bands between 25.5 GHz and 32.5 GHz and it provides an axial ratio bandwidth of 1.5 GHz from 27.25GHz to 28.75GHz, which will be deployed in the U.S. and Canada. In addition, a performance and analysis of the MIMO performance measures for the proposed architecture have been presented. An antenna prototype is built and tested to validate simulation results.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.059
GPT teacher head0.356
Teacher spread0.297 · 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.

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

Citations5
Published2022
Admission routes1
Has abstractyes

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