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Record W4324290742 · doi:10.1109/tcsii.2023.3257168

A Highly-Efficient Doherty Power Amplifier With Generalized Parallel-Circuit Class-EF Mode

2023· article· en· W4324290742 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

VenueIEEE Transactions on Circuits & Systems II Express Briefs · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsUniversity of CalgaryPolytechnique Montréal
FundersNorthwestern Polytechnical UniversityNational Natural Science Foundation of China
KeywordsAmplifierHigh-electron-mobility transistorDoherty amplifierElectrical engineeringTopology (electrical circuits)TransistorOffset (computer science)Power (physics)HarmonicMaterials scienceElectronic engineeringOptoelectronicsRF power amplifierComputer scienceEngineeringPhysicsVoltageAcoustics

Abstract

fetched live from OpenAlex

In this brief, a highly-efficient Doherty power amplifier (DPA) architecture with generalized parallel-circuit class-EF mode is proposed. With this topology, the ideal harmonic impedance conditions at the deep power back-off (PBO) region and saturation region can remain the same. Based on it, by adding a single harmonic control network (HCN) and an offset line, the carrier PA can be operated at the ideal high-efficiency conditions within the above two regions. In this case, the overall efficiency of the DPA can be improved simultaneously. As an example, a high-efficiency DPA working at 2.6 GHz is designed and fabricated based on a Wolfspeed CGH40010F GaN HEMT transistor. The measured results of the proposed structure demonstrated that a drain efficiency (DE) of 76.7% with the peak outpower of 45.2 dBm, as well as DE of 74.8% at the 6dB power back off region.

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: Empirical · Consensus signal: none
Teacher disagreement score0.938
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.023
GPT teacher head0.234
Teacher spread0.212 · 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