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Record W2808301541 · doi:10.1109/lmwc.2018.2843160

60-GHz Power Amplifier in 45-nm SOI-CMOS Using Stacked Transformer-Based Parallel Power Combiner

2018· article· en· W2808301541 on OpenAlexafffund
Jingjing Xia, Xiaohu Fang, Slim Boumaiza

Bibliographic record

VenueIEEE Microwave and Wireless Components Letters · 2018
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAmplifierCMOSPower dividers and directional couplersElectrical engineeringExtremely high frequencyTransformerSilicon on insulatorInductanceElectric power transmissionMaterials scienceOptoelectronicsElectronic engineeringEngineeringSiliconTelecommunicationsVoltage

Abstract

fetched live from OpenAlex

This letter presents the design of a 60-GHz power amplifier (PA) using a new stacked transformer (STF)-based parallel combiner. It begins by highlighting the main limitation of the conventional millimeter-wave (mm-wave) transformer-based parallel combiners, namely, the output parasitic transmission lines. Then, a new STF parallel combiner based on three overlaying coils is proposed. Analyses revealed significant enhancements in terms of self-inductance, quality factors, and coupling factors, which lead to enhanced combining efficiency in the proposed combiner. Subsequently, a two-stage mm-wave PA is implemented in 45-nm silicon-on-insulator CMOS technology. The fabricated PA demonstrates a 3-dB bandwidth equal to 12.5 GHz (50-62.5 GHz). The output power at 1-dB compression/saturation (OP1dB/Psat) and the corresponding power-added efficiencies are recorded as 16.2/18.5 dBm and 18.7/25.5%, 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 science0.0000.000
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 head0.023
GPT teacher head0.224
Teacher spread0.201 · 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

Citations31
Published2018
Admission routes2
Has abstractyes

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