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Record W2042416520 · doi:10.1109/pawr.2014.6825724

High efficiency two-stage GaN power amplifier with improved linearity

2014· article· en· W2042416520 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
KeywordsLinearityAmplifierGallium nitrideHigh-electron-mobility transistorAdjacent channelTransistorElectronic engineeringMaterials scienceBroadbandComputer sciencedBmCascodeOptoelectronicsBandwidth (computing)Electrical engineeringVoltageEngineeringTelecommunications

Abstract

fetched live from OpenAlex

In this paper, we propose a systematic approach to designing a highly efficient two-stage power amplifier (PA) with improved linearity. Investigation into the sources of nonlinearity in gallium nitride (GaN) high electron mobility transistors (HEMT) has been essential prior to the development of the two-stage PA design with improved linearity. A prototype was designed and fabricated using 45W and 6W packaged CREE transistors as the main and driver stages respectively. A peak efficiency of about 70% was obtained, using a continuous wave stimulus, over a bandwidth of 200MHz. When driven with a 20MHz WCDMA signal, at 800MHz, an adjacent channel leakage power ratio (ACLR) of 46dBc and an error vector magnitude (EVM) of about 1.5% were recorded at a peak output power of 39dBm without the use of digital pre-distortion (DPD). These results represent an improvement of about 10dB in ACLR and 2% in EVM for the two-stage PA using nonlinear driver as compare to those obtained using a linear driver.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.901
Threshold uncertainty score0.884

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)0.0010.000

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 head0.006
GPT teacher head0.207
Teacher spread0.201 · 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

Citations8
Published2014
Admission routes1
Has abstractyes

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