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Record W2147070752 · doi:10.23919/eumc.2009.5295940

A novel design method of highly efficient saturated power amplifier based on self-generated harmonic currents

2009· article· en· W2147070752 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAmplifierdBcHarmonicElectrical engineeringPower (physics)High-electron-mobility transistorWaveformSIGNAL (programming language)Materials scienceDoherty amplifierTransistorHarmonic analysisVoltagePower-added efficiencyElectronic engineeringRF power amplifierComputer scienceOptoelectronicsPhysicsAcousticsEngineeringCMOS

Abstract

fetched live from OpenAlex

A novel design method without requiring the special harmonic termination circuit for a highly efficient power amplifier (PA) is proposed. The proposed PA is driven into saturated operation, from the linear to knee region, by adjusting the only fundamental load, and the saturated operation induces self-generated harmonic currents. The current and voltage waveforms can be shaped easily by the harmonic currents, and efficiency of the PA is maximized. From the proposed design concept, a PA is implemented using 45-W GaN HEMT device at 2.655 GHz. The designed PA has a maximum drain efficiency of 71.5% at a saturated output power of 46.8 dBm for CW signal. The PA can be linearized to −46 dBc using the WDFBPD technique for a mobile WiMAX 2FA signal.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.645
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 head0.025
GPT teacher head0.269
Teacher spread0.244 · 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

Quick stats

Citations10
Published2009
Admission routes1
Has abstractyes

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