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Record W1985115043 · doi:10.1116/1.2180269

Parasitics-aware layout design of a low-power fully integrated complementary metal-oxide semiconductor power amplifier

2006· article· en· W1985115043 on OpenAlexaff
Samar M. Abdelsayed, M. Jamal Deen, Natalia K. Nikolova

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2006
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsMcMaster University
Fundersnot available
KeywordsParasitic extractionCMOSInterconnectionAmplifierElectronic engineeringIntegrated circuitPower (physics)Electrical engineeringElectronic circuitEngineeringComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

There is a need for efficient fully integrated complementary metal-oxide semiconductor (CMOS) power amplifiers (PAs) for very low power implanted biomedical transceiver systems. However, the parasitics of on-silicon interconnections can cause significant degradation in the performance of radio frequency integrated circuits, in general, and PAs, in particular. In this article, we propose a special layout design approach, which was used to design the layout of a CMOS PA. This approach relies on modeling the interconnection wires in the simulations and optimizing their widths for minimum parasitic effects and hence optimum measured circuit performance. The PA circuit is operating at 2.45GHz and is implemented in a standard 0.18μm CMOS process. Measurement results show that at a supply voltage of 1.4V, the PA delivers an output power of 4.5mW with 28.5% power-added efficiency and a power gain of 21.5dB. Owing to the careful layout design and interconnection optimization, the implemented PA circuit shows good efficiency and demonstrates a good match between the measured and simulated performance characteristics.

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)0.001
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 score0.016
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.226
Teacher spread0.215 · 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

Citations2
Published2006
Admission routes1
Has abstractyes

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