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Record W1978112103 · doi:10.1109/tvlsi.2014.2334642

A Sub-mW, Ultra-Low-Voltage, Wideband Low-Noise Amplifier Design Technique

2014· article· en· W1978112103 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Very Large Scale Integration (VLSI) Systems · 2014
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsMcGill University
Fundersnot available
KeywordsCMOSLow-noise amplifierWidebandElectrical engineeringAmplifierElectronic engineeringNoise figureBandwidth (computing)Integrated circuit designBiasingPhysicsComputer scienceVoltageEngineeringTelecommunications

Abstract

fetched live from OpenAlex

This paper presents a design methodology for an ultra-low-power (ULP) and ultra-low-voltage (ULV) ultra-wideband (UWB) resistive-shunt feedback low-noise amplifier (LNA). The ULV circuit design challenges are discussed and a new biasing metric for ULV and ULP designs in deep-submicrometer CMOS technologies is introduced. Series inductive peaking in the feedback loop is analyzed and employed to enhance the bandwidth and noise performance of the LNA. Exploiting the new biasing metric, the design methodology, and series inductive peaking in the feedback loop, a 0.5 V, 0.75-mW broadband LNA with a current reuse scheme is implemented in a 90-nm CMOS technology. Measurement results show 12.6-dB voltage gain, 0.1-7-GHz bandwidth, 5.5-dB NF, -9-dBm IIP <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> , and -18-dB P1dB while occupying 0.23 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> .

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.989
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.011
GPT teacher head0.209
Teacher spread0.198 · 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