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Record W3019200808 · doi:10.1109/access.2020.2989377

Design of a Compact Microstrip Triple Independently Controlled Pass Bands Filter for GSM, GPS and WiFi Applications

2020· article· en· W3019200808 on OpenAlexaff
Abdul Basit, Muhammad Irfan Khattak, Abdel-Razik Sebak, Abdul Baseer Qazi, Ahmad A. Telba

Bibliographic record

VenueIEEE Access · 2020
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsConcordia University
FundersNational Plan for Science, Technology and Innovation
KeywordsGSMGlobal Positioning SystemComputer scienceMicrostripMicrostrip antennaBand-pass filterTelecommunicationsComputer networkElectronic engineeringEngineeringAntenna (radio)

Abstract

fetched live from OpenAlex

An ultra-compact triple-band bandpass filter based on dual-mode quarter-wave resonator for GSM, GPS, and WiFi applications is presented in this study. The filter consists of three quarter-wave resonators assisting in controlling each passband independently. The first operating frequency band is obtained by the direct-feed resonator which acts as a source to load coupling for the inner two resonators which are operating at higher frequency bands. The outermost resonator is coupled to the inner loaded resonators, thus a pair of transmission zeros between each passband can be excited and hence high-frequency selectivity can be obtained. To miniaturize the overall size of the filter, all resonators are folded and are jointly connected through a common metallic via with the ground. The design has a symmetric structure therefore, even-odd mode analysis method is applied to obtain the three controllable operating frequency bands. The first operating band is centered at 850 MHz which caters for GSM applications, while the second and third frequency bands centered at 1.57 GHz and 2.4 GHz fall in the GPS and WiFi wireless applications. The filter with an ultra-compact size of 0.10 λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">g</sub> × 0.09 λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">g</sub> (0.009λ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">g</sub> ) despite feed lines (λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">g</sub> is the waveguide length centered at 850 MHz) is designed, fabricated and measured for the purpose of validation. Both the simulated and measured results are in good agreement and endorse the design concept.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score0.595

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 head0.039
GPT teacher head0.264
Teacher spread0.225 · 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

Citations23
Published2020
Admission routes1
Has abstractyes

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