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Record W2790387962 · doi:10.1049/iet-cds.2017.0507

Low‐power low data rate FM‐UWB receiver front end

2018· article· en· W2790387962 on OpenAlex
Sean E. Whitehall, Carlos E. Saavedra

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIET Circuits Devices & Systems · 2018
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRF front endAmplifierEnvelope detectorCMOSElectrical engineeringSIGNAL (programming language)Front and back endsRadio receiver designIntermediate frequencyWidebandEngineeringElectronic engineeringRadio frequencyChannel (broadcasting)Computer scienceTransmitter

Abstract

fetched live from OpenAlex

This study introduces a frequency modulated ultra‐wideband (FM‐UWB) receiver optimised for low power and fast start‐up. The receiver consists of a front end amplifier converting a frequency modulated signal to an amplitude modulated signal which is applied to an envelope detector. The receiver front end is for 500 MHz channels centred at 3450 and 3950 MHz. The amplifier uses passive gain and four cascaded gain stages to achieve high radio‐frequency gain without the need for super‐regeneration. By simplifying the architecture this way, the front end has a 5 μs wake‐up time to enable efficient duty‐cycling. The measured front end receives a signal at −68 dBm while consuming 600 μW of power (excluding a test buffer) from a 1 V supply. Fabrication was done using the IBM 130‐nm CMOS technology on a 1 mm × 1 mm loose die.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.808
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.006

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 head0.026
GPT teacher head0.237
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