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Record W3008018479 · doi:10.1049/iet-map.2019.0630

Frequency reconfigurable Yagi‐like MIMO antenna system with a wideband reflector

2020· article· en· W3008018479 on OpenAlexaff
Syed S. Jehangir, Rifaqat Hussain, Mousa Hussein, Mohammad S. Sharawi

Bibliographic record

VenueIET Microwaves Antennas & Propagation · 2020
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsWidebandReflector (photography)Reconfigurable antennaMIMOAntenna (radio)Electronic engineeringComputer sciencePhysicsOpticsTelecommunicationsDipole antennaEngineeringCoaxial antennaBeamforming

Abstract

fetched live from OpenAlex

A compact single layer frequency reconfigurable Yagi‐like multiple‐input multiple‐output (MIMO) antenna system is presented based on a half‐ring closed loop slot excitation. The traditional omnidirectional pattern of a slot antenna is made directional by using a single slot‐based complementary wideband reflector (CWBR) element. The proposed CWBR is compact in size, simple in construction, and is based on a single‐layer geometry unlike complex multi‐layer reflectors used in the literature. It improves the front‐to‐back ratio between 5 and 17 dB in the entire frequency range covering 2.5–4.5 GHz. The proposed reconfigurable MIMO antenna system covers the LTE and WiMAX bands with a minimum measured bandwidth of 200 MHz per covered bands. The frequency reconfigurability is achieved by reactively loading the slot loop with varactor diodes. The overall size of the proposed antenna system is , making it suitable for tablet handheld devices and access points. It has a maximum measured peak gain of 5 dBi and total measured radiation efficiency of 78%. The proposed MIMO antenna system has port isolation of 10 dB within the entire band of operation. The radiation patterns are isolated in space from each other and ensure very low envelope correlation coefficient.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.781
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.198
Teacher spread0.184 · 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
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

Citations7
Published2020
Admission routes1
Has abstractyes

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