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Record W2131489601 · doi:10.1109/issse.2007.4294448

Impact of PA Mismatching in Chireix-Outphasing System without Stubs

2007· article· en· W2131489601 on OpenAlexaff
M. El-Asmar, A. Birafane, Ammar B. Kouki

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsReactanceLinearityElectrical impedanceShunt (medical)SoftwareImpedance matchingComputer scienceWidebandElectronic engineeringAcousticsPhysicsEngineeringElectrical engineeringVoltage

Abstract

fetched live from OpenAlex

In this paper; new expressions for the Chireix combiner without stubs are derived to study the impact of the combiner mismatching to the efficiency and the linearity of the system. We show analytically that the Chireix outphasing combiner without the shunt reactance is perfectly linear but the instantaneous efficiency degrades when impedance mismatching between the combiner and the PA occurs. We varied the length and the impedance of the λ/4 transmission line of the Chireix combiner consequently we can see by using ADS software that the system stays linear and the best efficiency exist at length of λ/4 and impedance of 1.4Z0. In the other hand, we note that the efficiency is reduced and is at the best equal to that of the hybrid combiner. This work is validated through simulation with ADS software using CDMA and multi-tones and one tone 2GHz envelope modulated signals.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.010
GPT teacher head0.279
Teacher spread0.269 · 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 designSimulation or modeling
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

Citations8
Published2007
Admission routes1
Has abstractyes

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