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Record W2047162269 · doi:10.1109/tmtt.2011.2178259

An Ultra-Low-Voltage and Low-Power $\times$2 Subharmonic Downconverter Mixer

2012· article· en· W2047162269 on OpenAlexaff
Shan He, Carlos E. Saavedra

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2012
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsQueen's University
Fundersnot available
KeywordsTransconductanceMESFETHarmonic mixerGilbert cellElectronic mixerFrequency mixerTopology (electrical circuits)Electrical engineeringCMOSTransistorLocal oscillatorElectronic engineeringComputer scienceVoltageAmplifierEngineeringRadio frequencyField-effect transistor

Abstract

fetched live from OpenAlex

An 8.6 GHz$\times$2 subharmonic mixer with complementary current-reuse to enable ultra-low-voltage and low-power operation is presented. The RF transconductance stage of the mixer uses inductive source degeneration and the mixing core uses four transistors that are driven by a quadrature LO signal. A Volterra series analysis is carried out to determine the optimal gate biasing of the transconductor circuit to maximize the third-order intercept point$({\hbox{IIP}}_{3})$performance of the RF stage and of the entire mixer. Experimental results show that the mixer has a conversion gain of 6.0 dB and an${\hbox{IIP}}_{3}$of$-$8.0 dBm. The entire circuit draws 0.6 mW from a 0.6 V supply. The chip was fabricated in a standard 130 nm CMOS process.

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 score0.004
Threshold uncertainty score0.012

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.006
GPT teacher head0.212
Teacher spread0.206 · 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

Citations30
Published2012
Admission routes1
Has abstractyes

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