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Record W2155671931 · doi:10.1109/tcsi.2006.885980

RF Class-D Amplification With Bandpass Sigma–Delta Modulator Drive Signals

2006· article· en· W2155671931 on OpenAlexaff
Thomas Johnson, S.P. Stapleton

Bibliographic record

VenueIEEE Transactions on Circuits and Systems I Fundamental Theory and Applications · 2006
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAmplifierPower-added efficiencyDelta-sigma modulationRF power amplifierPhysicsCommon sourceElectrical engineeringTransistorElectronic engineeringEngineeringVoltageCMOS

Abstract

fetched live from OpenAlex

The power efficiency of a RF Class-D amplifier with a bandpass sigma-delta (SigmaDeltaM) modulator is analyzed for a complementary voltage-switched configuration. The modulator broadens the application of the amplifier to include signals with time varying envelopes such as W-CDMA. The addition of a modulator introduces new design variables which affect amplifier power efficiency including coding efficiency and the average transition frequency of the pulse train. Design equations are derived for the optimum load impedance, output power, conduction losses, capacitive switching losses, and drain efficiency. The general design equations are consistent with both periodic and aperiodic drive signals. Analytic and simulated results are compared for an example design with pseudomorphic high-electron mobility transistor and metal-semiconductor field-effect transistor switches with a fourth-order bandpass SigmaDeltaM. The results show a drain efficiency of 52% with a 10-dB peak-to-average power ratio W-CDMA source signal at a frequency of 500 MHz

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 head0.018
GPT teacher head0.225
Teacher spread0.207 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations119
Published2006
Admission routes1
Has abstractyes

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