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Record W2153816103 · doi:10.1109/eumc.2006.281239

On the Robustness of the Predistortion Function Synthesis for Highly Nonlinear RF Power Amplifiers Linearization

2006· article· en· W2153816103 on OpenAlex

Why this work is in the frame

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affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPredistortionAmplifierRobustness (evolution)LinearizationRF power amplifierComputer scienceLinearityPolynomial and rational function modelingAdjacent channelPolynomialAdjacent channel power ratioElectronic engineeringNonlinear systemAlgorithmNonlinear distortionControl theory (sociology)MathematicsTelecommunicationsEngineeringBandwidth (computing)PhysicsMathematical analysisArtificial intelligence

Abstract

fetched live from OpenAlex

This paper investigates the robustness of the digital predistortion function synthesis process applied to linearize a highly non linear RF power amplifier. For this purpose, a 100-watts peak power amplifier designed for UMTS applications biased in deep class AB is used. Two approaches have been compared: the polynomial curve fitting of the measured AM/AM and AM/PM characteristics and the look-up tables synthesis using the smoothed versions of these same non linear curves. The polynomial based fitting presents badly conditioned matrices that make this approach unpractical for the considered non linearity shape particularly for DSP implementation of the synthesis procedure. The accuracy of both approaches was assessed by measuring the adjacent channel power ratio at the output of the power amplifier under a 2-carriers W-CDMA signal. The look-up tables approach based on the averaging technique showed better correction capabilities than the polynomial based fitting

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 score0.964
Threshold uncertainty score0.347

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 head0.008
GPT teacher head0.187
Teacher spread0.179 · 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

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Citations4
Published2006
Admission routes2
Has abstractyes

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