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Record W2169320237 · doi:10.1109/tmtt.2011.2169277

Broadband Low-Noise Amplifier With Fast Power Switching for 3.1–10.6-GHz Ultra-Wideband Applications

2011· article· en· W2169320237 on OpenAlexafffund
Ahmed M. El‐Gabaly, Carlos E. Saavedra

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2011
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsQueen's University
FundersUniversity of WaterlooCMC Microsystems
KeywordsJitterWidebandElectrical engineeringAmplifierResistorCMOSNoise (video)Phase noisePhysicsNoise temperatureElectronic engineeringVoltageEngineeringComputer science

Abstract

fetched live from OpenAlex

A novel fast switching noise-cancelling low-noise amplifier (LNA) is presented in this paper using 0.13-μ m CMOS for 3.1-10.6-GHz ultra-wideband applications. A new noise-cancelling topology is employed to simultaneously achieve a sub-4-dB flat noise figure and a high gain of 16.6 dB for frequencies up to 10 GHz. Fast on and off power switching is achieved by bypassing the large dc-bias resistors that lead to long charging time constants, allowing the output voltage to settle within only 1.3 ns for switching frequencies as high as 200 MHz. The phase noise and jitter added by the switched LNA was characterized, and the measured output integrated rms jitter is about 750 fs from 10 Hz to 1 MHz, while the input integrated rms jitter is 420 fs. The circuit consumes 18 mW of dc power in the on state. When the circuit is switched on and off with a 50% duty cycle, the power consumption is less than 10 mW. It occupies an active chip area of less than 0.5 mm2.

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: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0010.001

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 head0.208
Teacher spread0.197 · 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

Citations29
Published2011
Admission routes2
Has abstractyes

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