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Record W4378514948 · doi:10.3390/mi14051010

A Low-Phase-Noise 8 GHz Linear-Band Sub-Millimeter-Wave Phase-Locked Loop in 22 nm FD-SOI CMOS

2023· article· en· W4378514948 on OpenAlexaff
Mamady Kebe, Mihai Sanduleanu

Bibliographic record

VenueMicromachines · 2023
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsUniversity of Ottawa
FundersKhalifa University of Science, Technology and Research
KeywordsPhase noisedBcWidebandVoltage-controlled oscillatorPhase-locked loopMaterials scienceCMOSAmplifierElectrical engineeringOptoelectronicsVoltageEngineering

Abstract

fetched live from OpenAlex

Low-phase noise and wideband phased-locked loops (PLLs) are crucial for high-data rate communication and imaging systems. Sub-millimeter-wave (sub-mm-wave) PLLs typically exhibit poor performance in terms of noise and bandwidth due to higher device parasitic capacitances, among other reasons. In this regard, a low-phase-noise, wideband, integer-N, type-II phase-locked loop was implemented in the 22 nm FD-SOI CMOS process. The proposed wideband linear differential tuning I/Q voltage-controlled oscillator (VCO) achieves an overall frequency range of 157.5–167.5 GHz with 8 GHz linear tuning and a phase noise of −113 dBc/Hz @ 100 KHz. Moreover, the fabricated PLL produces a phase noise less than −103 dBc/Hz @ 1 KHz and −128 dBc/Hz @ 100 KHz, corresponding to the lowest phase noise generated by a sub-millimeter-wave PLL to date. The measured RF output saturated power and DC power consumption of the PLL are 2 dBm and 120.75 mW, respectively, whereas the fabricated chip comprising a power amplifier and an integrated antenna occupies an area of 1.25 × 0.9 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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 communication0.0000.000
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 head0.023
GPT teacher head0.265
Teacher spread0.242 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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