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Record W2139547618 · doi:10.1109/jssc.2014.2319259

A 19 dBm, 15 Gbaud, 9 bit SOI CMOS Power-DAC Cell for High-Order QAM W-Band Transmitters

2014· article· en· W2139547618 on OpenAlexaff
Stefan Shopov, Andreea Balteanu, Sorin P. Voinigescu

Bibliographic record

VenueIEEE Journal of Solid-State Circuits · 2014
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCMOSPhysicsQuadrature amplitude modulationTransmitterElectrical engineeringdBmAmplitude modulationOpticsElectronic engineeringOptoelectronicsBit error rateEngineeringRadio frequencyFrequency modulationChannel (broadcasting)

Abstract

fetched live from OpenAlex

A mm-wave I-Q power-DAC is reported at W-band. The circuit, which is fabricated in a 45 nm SOI CMOS technology, employs a series-stacked Gilbert-cell output stage with gate finger geometry segmentation to directly modulate a 85-95 GHz carrier. The Gilbert-cell provides phase inversion and 7 bits for ASK envelope modulation, each of which can be switched at speeds up to 15 Gb/s. A ninth bit turns the entire DAC cell on and off at 15 Gb/s, as needed to create an arbitrary 15 Gbaud QAM constellation in a symmetrical 4×4 I-Q power-DAC transmitter array, with free-space power combining and antenna-level segmentation. The measured output power and PAE of the I or Q DAC cells are 19 dBm and 8.9%, respectively. Three effective bits of amplitude resolution and one phase bit are estimated from the small-signal S-parameter measurements in the 80-95 GHz range. The envelope amplitude resolution reduces to only two effective bits under saturated output power operation. The OOK bit provides over 45 dB of measured attenuation and dynamic range, relative to the peak output power.

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 score0.003
Threshold uncertainty score0.009

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)0.0030.001

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 head0.011
GPT teacher head0.222
Teacher spread0.211 · 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

Citations36
Published2014
Admission routes1
Has abstractyes

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