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Record W2296286855 · doi:10.1109/embc.2015.7320032

Ultra low-power transceiver with novel FSK modulation technique and efficient FSK-to-ASK demodulation

2015· article· en· W2296286855 on OpenAlexafffund
Mohamed Zgaren, Arash Moradi, Mohamad Sawan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsPolytechnique Montréal
FundersCanada Research ChairsCMC Microsystems
KeywordsFrequency-shift keyingDemodulationAmplitude-shift keyingTransceiverTransmitterElectrical engineeringElectronic engineeringCMOSOn-off keyingModulation (music)Ask priceComputer scienceEngineeringTelecommunicationsBit error rateChannel (broadcasting)Quadrature amplitude modulationPhase-shift keyingPhysics

Abstract

fetched live from OpenAlex

Energy-efficient and high-data rate are desired in biomedical devices transceivers. A high-performance transmitter (Tx) and an ultra-low-power receiver (Rx) dedicated to medical implants communications operating at Industrial, Scientific and Medical (ISM) frequency band are presented. Tx benefits from a new efficient Frequency-Shift Keying (FSK) modulation technique which provides up to 20 Mb/s of data-rate and consumes only 0.084 nJ/b validated through fabrication. The receiver consists of an FSK-to-ASK conversion based receiver with OOK fully passive wake-up device (WuRx). This WuRx is battery less with energy harvesting technique which plays an important role in making the RF transceiver energy-efficient. The Rx is achieved with a reduced hardware architecture which does not use an accurate local oscillator, high-Q external inductor and I/Q signal path. The Rx shows -78 dBm sensitivity for 8 Mbps data rate while consuming 639 μW. The proposed circuits are implemented in IBM 0.13 μm CMOS technology with 1.2 V supply voltage.

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 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 score0.675
Threshold uncertainty score0.744

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 head0.013
GPT teacher head0.198
Teacher spread0.186 · 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.

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

Citations3
Published2015
Admission routes2
Has abstractyes

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