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Record W2023813874 · doi:10.1109/tcsi.2013.2283781

Electronically Tunable Doherty Power Amplifier for Multi-Mode Multi-Band Base Stations

2013· article· en· W2023813874 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 and Systems I Regular Papers · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAmplifierDoherty amplifierWidebandPower (physics)Computer scienceElectronic engineeringElectrical engineeringMode (computer interface)RF power amplifierEngineeringTelecommunicationsBandwidth (computing)Physics

Abstract

fetched live from OpenAlex

This paper proposes an electronically reconfigurable Doherty amplifier capable of efficiently amplifying multi-standard multi-band wireless signals centered at widely spaced frequencies. The paper outlines closed form equations for an effective design methodology of frequency agile Doherty amplifiers driven with multi-mode signals using a small number of electronically tunable devices. As a proof of concept, a reconfigurable Doherty prototype is designed and fabricated to operate at 1.9, 2.14, and 2.6 GHz meant to efficiently amplify signals with peak-to-average power ratio equal to 6, 9 and 12 dB. The measurement results obtained using continuous wave signals reveal drain efficiencies of about 67% and 42% at the peak power and 12 dB output back off power respectively for the three operating frequencies. In addition, the reconfigurable Doherty amplifier is successfully linearized when driven with 20 MHz wideband code-division multiple access and 20 MHz long term evolution signals, using a Volterra based digital predistrtion algorithm which exploits a pruned Volterra series.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.985
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.251
Teacher spread0.224 · 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