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Record W2108923702 · doi:10.1109/mwsym.2013.6697626

Reconfigurable Doherty amplifier for efficient amplification of signals with variable PAPR

2013· article· en· W2108923702 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
KeywordsPredistortionAmplifierAdjacent channel power ratioDoherty amplifierElectronic engineeringdBcPower (physics)Crest factorComputer scienceElectrical engineeringBandwidth (computing)EngineeringRF power amplifierTelecommunicationsCMOSPhysics

Abstract

fetched live from OpenAlex

This paper proposes a reconfigurable Doherty amplifier capable of efficiently amplifying signals with variable peak-to-average power ratios (PAPR). A small number of electronically tunable devices are used to preserve appropriate Doherty load modulation as the input signal PAPR varies. A reconfigurable Doherty amplifier demonstrator was designed and fabricated, using gallium nitride transistors, to operate at 2.6 GHz and to efficiently amplify signals with PAPR of 6, 9 and 12 dB. Continuous wave measurements revealed power added efficiencies of higher than 64% at 6 and 9 dB and 59% at 12 dB output back-off. A Volterra based digital predistortion technique was also applied to examine the linearizability of the demonstrator and an Adjacent Channel Power Ratio (ACPR) of better than 46 dBc was achieved using 20MHz excitation signals with different PAPR values.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.820
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)0.0010.000

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 head0.014
GPT teacher head0.212
Teacher spread0.198 · 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

Citations5
Published2013
Admission routes1
Has abstractyes

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