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Record W2053488933 · doi:10.1109/rws.2007.351807

Wide Band Room Temperature 0.35-dB Noise Figure LNA in 90-nm Bulk CMOS

2007· article· en· W2053488933 on OpenAlexaffabout
Leonid Belostotski, J.W. Haslett

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCMOSLow-noise amplifierNoise figureAmplifierElectrical engineeringPhysicsBandwidth (computing)OptoelectronicsRangingElectronic engineeringMaterials scienceComputer scienceEngineeringTelecommunications

Abstract

fetched live from OpenAlex

Design and measurements of a room temperature 700 MHz - 1400 MHz low noise amplifier (LNA) in 90-nm bulk CMOS, intended for use in the Canadian large adaptive reflector (CLAR) radio telescope, are presented. The new bandwidth constrained LNA noise figure optimization and broad-banding technique as well as the importance of substrate shielding are discussed. The amplifier has 0.35 dB noise figure while consuming 45 mW of power from a 1-V supply and achieves output P1dB of -5.3 dBm and output IP3 of 7.5 dBm with the gain (S21) ranging from 20.5 dB to 16.3 dB across the band. The LNA's input and output impedances are matched to 50 Omega. The LNA represents the first CMOS design that satisfies the very demanding requirements of radio telescopes. The topology and optimization presented in this paper are not limited to radio astronomy applications and can be applied for wide band commercial applications such as tri-band GSM operating in the 850 MHz - 1900 MHz frequency range

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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.002

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 head0.007
GPT teacher head0.202
Teacher spread0.195 · 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

Citations27
Published2007
Admission routes2
Has abstractyes

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Same topicRadio Frequency Integrated Circuit DesignFrench-language works237,207