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Record W2761443731 · doi:10.1109/mwsym.2017.8058965

A wideband millimeter-wave differential stacked-FET power amplifier with 17.3 dBm output power and 25% PAE in 45nm SOI CMOS

2017· article· en· W2761443731 on OpenAlexaff
Jingjing Xia, Arthur Chung, Slim Boumaiza

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsUniversity of Waterloo
FundersKeysight Technologies
KeywordsAmplifierElectrical engineeringWidebandCMOSExtremely high frequencySilicon on insulatorTransistorPower-added efficiencyBandwidth (computing)TransformerMaterials scienceRF power amplifierOptoelectronicsElectronic engineeringEngineeringVoltageSiliconTelecommunications

Abstract

fetched live from OpenAlex

This paper presents the design of an efficient two-stage m illim eter-wave power amplifier (PA) using stacked field-effect transistors in 45nm silicon-on-insulator (SOI) CMOS technology. It highlights two major issues encountered when designing single-ended multistage PAs at millimeter frequencies (e.g., 60GHz), namely the significant source to ground parasitic inductance and the vulnerability to oscillation at low frequencies. The two-stage differential PA includes input, inter-stage and output matching networks implemented using RF transformers with a high coupling factor and reduced insertion losses. The PA demonstrator showed a 3-dB bandwidth equal to 12GHz (55-67GHz). The small signal gain, peak power added efficiency and peak output power were recorded as 14.5dB, 25% and 17.3dBm, respectively.

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 score0.001
Threshold uncertainty score0.003

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.214
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

Citations10
Published2017
Admission routes1
Has abstractyes

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