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Record W1985149916 · doi:10.1109/rws.2010.5434205

Reconfigurable RF front-end for frequency-agile direct conversion receivers and cognitive radio system applications

2010· article· en· W1985149916 on OpenAlexafffund
Érick Emmanuel Djoumessi, Ke Wu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDemodulationFrequency agilityRF front endPhase-shift keyingWidebandVaricapElectrical engineeringRadio frequencyElectronic engineeringRadio receiver designCognitive radioQAMGSMBand-pass filterEngineeringComputer scienceTransmitterQuadrature amplitude modulationTelecommunicationsPhysicsBit error rateWirelessRadar

Abstract

fetched live from OpenAlex

A reconfigurable direct conversion receiver front-end for GSM and WLAN bands (1.9 and 2.4 GHz) is proposed and demonstrated for cognitive radio system applications. The RF front-end platform makes use of a silicon varactor-tuned bandpass filter in connection with a tunable six-port demodulator. Varactor diodes of both of the tunable structures are independently biased using two different sets of supply voltage. The demodulation of phase-shift-keying (PSK) signals at a bit rate of 40 Mbps is achieved by using wideband power detectors. An experimental test bench of the proposed receiver is realized, and QPSK and 8PSK signal constellations are measured at the center-operating frequencies of 1.9 and 2.4 GHz for different noise levels.

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 score0.007

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 communication0.0000.000
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 head0.009
GPT teacher head0.201
Teacher spread0.192 · 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

Citations11
Published2010
Admission routes2
Has abstractyes

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