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Record W4210988944 · doi:10.1109/lmwc.2022.3147432

Dual-Mode RF Mixer for Low-Power Direct-Conversion Receiver

2022· article· en· W4210988944 on OpenAlexafffund
C. Hannachi, Ke Wu

Bibliographic record

VenueIEEE Microwave and Wireless Components Letters · 2022
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRadio frequencyFrequency mixerRF power amplifierWidebandElectrical engineeringDirect-conversion receiverElectronic engineeringEnergy conversion efficiencyPower (physics)Intermediate frequencyPort (circuit theory)Multi-band deviceElectronic mixerEngineeringComputer scienceHarmonic mixerPhysicsLocal oscillatorAntenna (radio)AmplifierDetector

Abstract

fetched live from OpenAlex

In this work, a dual-mode (DM) radio frequency (RF) mixer is studied and validated over the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> -band to meet the ultralow-power requirement of direct-conversion receiver architectures. The proposed RF mixer combines two operation modes, namely, RF energy harvesting mode and RF mixing mode, which are implemented within a single passive multiport interferometric circuit. This approach aims at harvesting part of the RF energy for powering specific low-power active devices toward the energy autonomy of RF receiver systems. For this proof-of-concept study, a circuit is prototyped and tested. The experimental results show promising performance. Inter-port isolation better than 20 dB is achieved over a frequency range of 22–26 GHz, together with good RF-to-dc conversion efficiency (up to 45% with RF input power of 40 mW), and appreciable RF mixer conversion loss over a wideband (average 12.8 dB).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.144
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.195
Teacher spread0.187 · 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 teacher head, not a consensus.

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

Citations7
Published2022
Admission routes2
Has abstractyes

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