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Record W4233679578 · doi:10.1109/sbcci.2016.7724068

A 450 mV supply self-biased wideband inductorless balun LNA for sub-GHz applications

2016· article· en· W4233679578 on OpenAlexfundno aff
Arthur Liraneto Torres Costa, Hamilton Klimach, Sérgio Bampi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorConselho Nacional de Desenvolvimento Científico e TecnológicoNSCAD University
KeywordsCMOSWidebandElectrical engineeringParasitic extractionInductorBalunLow-noise amplifierPMOS logicAmplifierNMOS logicElectronic engineeringTransistorNoise figureEngineeringTopology (electrical circuits)VoltageComputer scienceAntenna (radio)

Abstract

fetched live from OpenAlex

This paper presents a CMOS wideband LNA topology operating under a 450 mV voltage supply in the analog TV white spaces frequency band from 54 MHz to 862 MHz. It could be used in a wideband RFID or energy harvesting communication network applications. The proposed circuit is self-biased, uses no inductors and it has a cascaded amplifier in the noise canceling branch for a better trade-off of noise figure (NF), S11 and IP3. The 450 mV operation is achieved by a proper choice of the basic amplifiers that compose the noise canceling topology. This paper demonstrates the use of low-VT PMOS transistors and zero-VT NMOS transistors in a RF circuit, in order to be self-biased in a 130 nm CMOS technology PDK from Global Foundries. The post-layout simulations included bondwire inductances and pad capacitances parasitics for more realistic results. Under such a low supply, the LNA circuit is capable of Voltage Gain > 17 dB, NF <; 6.2 dB and S11 <; -10.3 dB, in the 54 MHz - 862 MHz range. The overall LNA power consumption is only 2 mW.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 integrity0.0000.000
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 head0.013
GPT teacher head0.211
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

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
GenreMethods

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
Published2016
Admission routes1
Has abstractyes

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