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Record W2333026953 · doi:10.1109/rws.2016.7444389

Design methodology of high-efficiency contiguous mode harmonically tuned power amplifiers

2016· article· en· W2333026953 on OpenAlexaff
Tushar Sharma, Ramzi Darraji, Fadhel M. Ghannouchi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAmplifierGallium nitrideWaveformBroadbandPower (physics)TransistorElectrical impedanceElectronic engineeringReliability (semiconductor)VoltageElectrical engineeringPower-added efficiencyComputer scienceMaterials scienceEngineeringOperational amplifierPhysicsTelecommunications

Abstract

fetched live from OpenAlex

This paper presents a design methodology for high-efficiency broadband power amplifiers (PAs). The continuous class-F PA operation is extended to a contiguous set of voltage/current waveforms providing a design area for targeted drain efficiency of greater than 78.5%. The proposed methodology relaxes the design constraints by utilizing a different set of voltage waveforms in extracting the impedance design space while ensuring that the device operates below the limit of breakdown. As such, the proposed methodology provides device reliability under the broadband operation. For the experimental validation, Cree 10-W gallium nitride (GaN) transistor is used. The PA outputs more than 10W power with power added efficiency (PAE) greater than 75% with a peak PAE of 85%. This performance is achieved over the frequency band 550 to 950 MHz.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.054
GPT teacher head0.282
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations15
Published2016
Admission routes1
Has abstractyes

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