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Record W2139895053 · doi:10.1109/22.981268

A completely integrated 1.9-GHz receiver front-end with monolithic image-reject filter and VCO

2002· article· en· W2139895053 on OpenAlexaff
John Rogers, J. Macedo, Calvin Plett

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2002
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsCarleton UniversityBlackberry (Canada)CMC Microsystems (Canada)
Fundersnot available
KeywordsVoltage-controlled oscillatorElectrical engineeringSuperheterodyne receiverPhase noiseLocal oscillatorImage responseChipRF front endNoise figureInductorPhysicsMaterials scienceVoltageIntermediate frequencyOptoelectronicsEngineeringRadio frequencyAmplifierCMOS

Abstract

fetched live from OpenAlex

A 1.9-GHz monolithic superheterodyne receiver front-end with 300-MHz IF on-chip tunable image-reject filter and voltage-controlled oscillator (VCO) is presented. Two versions of the receiver were fabricated on a 0.5-/spl mu/m bipolar process and compared to a previously fabricated version with an off-chip VCO. The two versions are identical, except for the fact that the 2.2-GHz VCO was realized with and without ground-shielded inductors. The receiver that used ground-shielded inductors had a conversion gain of 25.6 dB, a noise figure of 4.5 dB, a third-order input intercept point (IIP3) of -19 dBm, an image rejection of 65 dB, and a phase noise of -103 dBc/Hz at 100-kHz offset. The receiver drew 32.5 mA from a 3-V supply and had a die area of 2.1 mm/spl times/1.7 mm. The local-oscillator-IF isolation improved compared to the previously fabricated front-end with an off-chip VCO.

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: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.015
GPT teacher head0.199
Teacher spread0.184 · 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

Citations14
Published2002
Admission routes1
Has abstractyes

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