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Record W2128769307 · doi:10.1109/iscas.2005.1465036

8 GHz Tunable CMOS Quadrature Generator using Differential Active Inductors

2005· article· en· W2128769307 on OpenAlexafffund
F. Mahmoudi, C.A.T. Salama

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPolyphase systemCMOSInductorQuadrature (astronomy)Electronic engineeringBandwidth (computing)Electrical engineeringComputer scienceEngineeringVoltageTelecommunications

Abstract

fetched live from OpenAlex

The design and implementation of a new 8 GHz tunable quadrature generator using a differential active inductor embedded in the local oscillator buffer are presented. The design has a much smaller form factor compared to the sequence asymmetric polyphase filter used as quadrature generator. It relaxes the coupling between the tuning of the output signal amplitude and quadrature phase and facilitates the application of automatic gain and phase control circuitry to compensate for process and temperature variations. It eliminates the need for additional buffering stages at the output of the quadrature generator and results in a considerable reduction in power consumption. A prototype implemented in 0.18 /spl mu/m CMOS technology, operating from a 1 V power supply and consuming 12 mW of power, features a measured gain of -2 dB and a worst case phase and amplitude mismatch of better than 1.5/spl deg/ and 1 dB respectively over a bandwidth of 100 MHz at 8 GHz. The design meets the potential specifications of 4G OFDM direct conversion receivers.

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 score0.002
Threshold uncertainty score0.008

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 communication0.0010.001
Open science0.0020.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.216
Teacher spread0.199 · 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

Citations10
Published2005
Admission routes2
Has abstractyes

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