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Record W7117319140 · doi:10.1109/jssc.2025.3643322

A Self-Injection <i>LC</i> Oscillator for Flicker Noise Reduction

2025· article· W7117319140 on OpenAlexafffund
Bahram Jafari, Ali Selk Ghafari, Sankaran Aniruddhan, Shahriar Mirabbasi, Sudip Shekhar

Bibliographic record

VenueIEEE Journal of Solid-State Circuits · 2025
Typearticle
Language
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhase noiseVoltage-controlled oscillatorLocal oscillatorFlicker noiseColpitts oscillatorDelay line oscillatorElectronic circuitVackář oscillatorCMOSElectronic oscillator

Abstract

fetched live from OpenAlex

Self-injection has been used in lasers and photonic integrated circuits to reduce the laser’s phase noise (PN). We show that self-injection can be leveraged in GHz <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LC</i> oscillators as well. Our oscillator employs a current-domain self-injection technique by leveraging second-harmonic extraction, capacitive phase shifting, and self-mixing through the oscillator’s bias path. The approach enables 90° phase-shifted injection completely on-chip, avoiding any bulky passive delay elements, and with only minor changes to the conventional class-B <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LC</i> oscillators. Thus, the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1/f^{3}$</tex-math> </inline-formula> corner can be reduced by at least an order of magnitude without any significant degradation in the tuning range or power consumption. Our proof-of-concept 4.6–6 GHz VCO in a 65 nm CMOS process achieves a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1/f^{3}$</tex-math> </inline-formula> PN corner of 5–35 kHz, and a peak figure-of-merit (FoM) of 193 dBc/Hz, as well as a FoM normalized by the tuning range of 201 dBc/Hz. At 4.64 GHz, the oscillator consumes 1.45 mA from a 1 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V$</tex-math> </inline-formula> supply and achieves−78.6 and −141.3dBc/Hz PN at 10kHz and 10MHz offsets, respectively. Across the measured tuning range of 26%, the oscillator maintains an excellent FoM performance in both the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1/f^{2}$</tex-math> </inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1/f^{3}$</tex-math> </inline-formula> regions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.719
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.287
Teacher spread0.270 · 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 teacher head, not a consensus.

Study designSimulation or modeling
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

Citations0
Published2025
Admission routes2
Has abstractyes

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