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Record W2151748373 · doi:10.1109/ccece.2006.277363

Low-Voltage Low-Power Low-Noise Amplifier for Wireless Sensor Networks

2006· article· en· W2151748373 on OpenAlexaff
Derek Ho, Shahriar Mirabbasi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsElectrical engineeringLow-noise amplifierAmplifierElectronic engineeringNoise figureCMOSEngineeringLow voltageComputer scienceVoltage

Abstract

fetched live from OpenAlex

This work presents a methodology for designing CMOS low-voltage low-power low-noise amplifiers (LNAs) based on the inductively degenerated common-source topology. To demonstrate the application of the proposed method, two LNAs operating at 900MHz and 2.4GHz are designed and simulated using a 90nm CMOS process. The 900MHz (2.4GHz) design has noise figure of less than 5.5dB (5dB) over the entire band of interest, a power gain of 12dB (13dB), input 1dB compression point of -20dBm (-18dBm), input-referred third-order intercept point of -10dBm (-9dBm), and consumes 1.6mW (2.8mW) from a 0.45V (0.5V) supply. Both LNAs are matched to 50Omega input and output impedances. The LNAs are designed for operation in the industrial, scientific, and medical (ISM) band and are intended for systems using the IEEE 802.15.4 (Zigbee) low-power standard

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.849
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)0.0010.000

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 head0.007
GPT teacher head0.195
Teacher spread0.188 · 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 designSimulation or modeling
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

Citations6
Published2006
Admission routes1
Has abstractyes

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