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Record W3077194662 · doi:10.1109/lssc.2020.3017075

A Reconfigurable Passive Switched-Capacitor TX RF Front End With −57 dB ACLR2

2020· article· en· W3077194662 on OpenAlexafffund
Konstantinos Vasilakopoulos, Antonio Liscidini

Bibliographic record

VenueIEEE Solid-State Circuits Letters · 2020
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsUniversity of Toronto
FundersAlexander S. Onassis Public Benefit FoundationCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaAnalog Devices
KeywordsCMOSBasebandElectrical engineeringFront and back endsAdjacent channelElectronic engineeringTransmitterRF front endSwitched capacitorComputer scienceRadio frequencyCapacitorAmplifierEngineeringChannel (broadcasting)

Abstract

fetched live from OpenAlex

This letter presents a wireless transmitter (TX) front end in which the functionalities of digital-to-analog conversion, baseband filtering, and signal upconversion are implemented by a passive switched-capacitor (PSC) network. The result is a versatile architecture that fully benefits from CMOS scaling. The front end was integrated in a 65-nm CMOS technology and can support various channel bandwidths simply by adjusting the switching frequency for the PSC network. Thanks to its third-order reconfigurable filter, it maintains a thermal noise floor better than -156 dBc/Hz at a power dissipation of 45 mW. The measured prototype achieves an ACLR2 of -57 dB and an EVM of -31 dB for a 20-MHz 64-QAM OFDM and a 20-MHz 16-QAM signal, 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 score0.002
Threshold uncertainty score0.007

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 communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.203
Teacher spread0.186 · 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

Citations6
Published2020
Admission routes2
Has abstractyes

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Same venueIEEE Solid-State Circuits LettersSame topicRadio Frequency Integrated Circuit DesignFrench-language works237,207