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Record W2132080901 · doi:10.1109/mwsym.2012.6259464

Novel wideband GaN HEMT power amplifier using microstrip radial stub to suppress harmonics

2012· article· en· W2132080901 on OpenAlexaff
Zhebin Wang, Chan-Wang Park

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsStub (electronics)WidebandHarmonicsAmplifierMicrostripHigh-electron-mobility transistordBcMaterials scienceBandwidth (computing)Electrical engineeringOptoelectronicsPhysicsEngineeringTransistorTelecommunicationsVoltage

Abstract

fetched live from OpenAlex

In this paper, a novel wideband GaN HEMT power amplifier (PA) using microstrip radial stub (MRS) in both input and output matching networks to suppress harmonic components of 2.14 GHz is analyzed, fabricated, and tested. The angle subtended by MRS and the bottom length of MRS are analyzed for harmonic suppressing purpose. The wideband harmonic suppressing characteristic of MRS is compared with normal 50 Ohm quarter-wave rectangular stub. The second and third harmonics of 2.14 GHz are suppressed by −38.37 dB and −29.53 dB, respectively. −15 dBc suppressing bandwidth over 1.32 GHz at both harmonic bands is obtained. By using the proposed MRS in both input and output matching network, the measured maximum power added efficiency (PAE) is 80.52% with 40.53 dBm output power at 2.14 GHz. At least 50% PAE and 37 dBm output power over a 12% bandwidth from 2 GHz to 2.26 GHz is achieved. The maximum gain is 20.25 dB.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.033
GPT teacher head0.262
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 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

Citations18
Published2012
Admission routes1
Has abstractyes

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