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Record W1987857235 · doi:10.1109/ccece.2012.6335008

A low current CMOS voltage regulator including RF desensitization for RFIC power amplifiers

2012· article· en· W1987857235 on OpenAlexafffund
Guy Ayissi Eyebe, Vahé Nerguizian, Nicolas Constantin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
FundersCMC Microsystems
KeywordsAmplifierRFICElectrical engineeringCascodeRF power amplifierCMOSOperational amplifierPower supply rejection ratioEngineeringTransistorElectronic engineeringVoltage

Abstract

fetched live from OpenAlex

This paper presents a CMOS voltage regulator employing an operational-amplifier operated from a 1.8V supply with very low current consumption, capable of delivering a stable regulated 1.4V output voltage with high enough current sourcing capability for the biasing of GaAs HBT RFIC power amplifiers, and subjected to strong RF perturbations. These features are particularly important in multi-technology RFIC power amplifier modules requiring advanced CMOS control functions for efficiency and linearity performance improvement, but having minimal RF signal isolation between the RF amplifier IC and the CMOS control IC, for compactness and cost considerations. The regulator design uses a recycled folded cascode operational-amplifier structure in a CMOS 0.18μm technology. The results presented show a total bias current of 135μA for the operational-amplifier, a current sourcing capability of 20mA when delivered to the equivalent load seen at the base of a power GaAs HBT RF transistor under 1.88GHz-20dBm excitation, and a drop of only 40mV in the regulated output voltage (97% regulation) when using an RF isolation inductor as small as 6nH.

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: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.031
GPT teacher head0.261
Teacher spread0.230 · 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

Citations0
Published2012
Admission routes2
Has abstractyes

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