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Record W2799902197 · doi:10.1109/cicc.2018.8357013

A low-power sub-GHz RF receiver front-end with enhanced blocker tolerance

2018· article· en· W2799902197 on OpenAlex
Zhonghong Jiang, D.A. Johns, Antonio Liscidini

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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBasebandRF front endElectrical engineeringCMOSNoise figureRadio frequencyTransistorPower (physics)RF power amplifierLow-power electronicsFront and back endsLow-noise amplifierSensitivity (control systems)Radio receiver designEngineeringElectronic engineeringPower consumptionPhysicsAmplifierTransmitterVoltage

Abstract

fetched live from OpenAlex

This paper presents a class-AB sub-GHz RF receiver front-end suitable for ultra-low power application. By exploiting transistors' class-AB operation in both the RF and baseband sections, the receiver front-end achieves a very low sensitivity and an elevated blocker tolerance while keeping a low power consumption. Such performance makes the receiver suitable for both short-range (e.g. 802.15.4) and long-range (e.g. LoRa) applications. The proposed RF front-end has been implemented in 0.13um CMOS technology, operates in the 868/915MHz ISM bands, and exhibits an in-band gain of 50dB, noise figure of 2.7dB, out-of-band HP3 of +2dBm, out-of-band IIP2 of +37dBm, out-of-band P1dB of -10.5dBm, while draining 2.1mA from a 1.2 V supply.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.452
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)0.0040.002

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 head0.006
GPT teacher head0.189
Teacher spread0.183 · 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

Quick stats

Citations12
Published2018
Admission routes1
Has abstractyes

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