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Record W2114221536 · doi:10.1109/mwsym.2011.5972885

A systematic methodology to design analog predistortion linearizer for dual inflection power amplifiers

2011· article· en· W2114221536 on OpenAlexaff
Saeed Rezaei, Mohammad Hashmi, Behzad Dehlaghi, Fadhel M. Ghannouchi

Bibliographic record

Venue2011 IEEE MTT-S International Microwave Symposium · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLinearizerPredistortionAmplifierSchottky diodeHybrid couplerElectronic engineeringIntermodulationAdjacent channel power ratioDiodePower (physics)Computer scienceElectrical engineeringEngineeringPower dividers and directional couplersPhysicsCMOS

Abstract

fetched live from OpenAlex

This paper presents a systematic methodology to design a diode-based RF predistortion linearizer that can be used to linearize power amplifiers with dual inflection points in their distortion characteristics. The proposed structure contains anti parallel configuration of Schottky diodes, complemented with a PIN diode in parallel, connected to through and coupled ports of a 90° hybrid coupler using λ/4 transmission lines. The use of a PIN diode in the linearizer provides it with an extra level of freedom in achieving the desired level of amplitude and inflection depth in the AM/AM characteristic. A systematic design procedure using this configuration is proposed and applied to linearize a commercial power amplifier. Two tone test experimental results show that the IM3 cancellation of 10 dB in 1 MHz separation between tones at 2.14 GHz can be achieved.

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)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.074
GPT teacher head0.279
Teacher spread0.204 · 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
GenreMethods

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

Citations15
Published2011
Admission routes1
Has abstractyes

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