Optimization of a low noise amplifier with two technology nodes using an interactive evolutionary approach
dc.contributor.author | DE LIMA MORETO, R. A. | |
dc.contributor.author | MARIANO A. | |
dc.contributor.author | THOMAZ, C. E. | |
dc.contributor.author | Salvador Gimenez | |
dc.contributor.authorOrcid | https://orcid.org/0000-0002-3616-9559 | |
dc.date.accessioned | 2022-01-12T21:54:36Z | |
dc.date.available | 2022-01-12T21:54:36Z | |
dc.date.issued | 2021-01-05 | |
dc.description.abstract | © 2021, Springer Science+Business Media, LLC, part of Springer Nature.Nowadays, wireless communications at frequencies of gigahertz have an increasing demand due to the ever-increasing number of electronic devices that uses this type of communication. However, the design of Radio Frequency (RF) circuits is difficult, time-consuming and based on designer knowledge and experience. This work proposes an interactive evolutionary approach based on genetic algorithm, implemented in the in-house iMTGSPICE optimization tool, to perform the optimization process of a Low-Power Low Noise Amplifier (LNA) dedicated to Wireless Sensor Networks (WSN), which is robust through the corner and Monte Carlo analyses and implemented in two Bulk CMOS technology nodes: 130 nm and 65 nm. Regarding each technology node, we performed two experimental studies to optimize the LNA. The first one used the conventional non-interactive approach of iMTGSPICE, which was not assisted by a designer during the optimization process. The second one used the interactive approach of iMTGSPICE, which was monitored and assisted by a beginner designer during the optimization process. The obtained results demonstrated that the interactive approach of iMTGSPICE performed the optimization process of the robust LNA from 16 to 94% faster than the non-interactive evolutionary approach. The design regarding the technology node of 130 nm took 341 min for the non-interactive and 20 min for the interactive optimization process, whereas the design in the 65 nm took 537 min for the non-interactive and 454 min for the interactive approach. | |
dc.description.firstpage | 307 | |
dc.description.issuenumber | 1 | |
dc.description.lastpage | 319 | |
dc.description.volume | 106 | |
dc.identifier.citation | DE LIMA MORETO, R. A.; MARIANO A.; THOMAZ, C. E.; GIMENEZ, S. Optimization of a low noise amplifier with two technology nodes using an interactive evolutionary approach. Analog Integrated Circuits and Signal Processing, v. 106, n. 1, p. 307-319, Jan. 2021. | |
dc.identifier.doi | 10.1007/s10470-020-01755-1 | |
dc.identifier.issn | 1573-1979 | |
dc.identifier.uri | https://repositorio.fei.edu.br/handle/FEI/3608 | |
dc.relation.ispartof | Analog Integrated Circuits and Signal Processing | |
dc.rights | Acesso Restrito | |
dc.subject.otherlanguage | Design of robust analog CMOS ICs | |
dc.subject.otherlanguage | Electronic design automation (EDA) | |
dc.subject.otherlanguage | Interactive genetic algorithm | |
dc.subject.otherlanguage | Low noise amplifier (LNA) | |
dc.title | Optimization of a low noise amplifier with two technology nodes using an interactive evolutionary approach | |
dc.type | Artigo | |
fei.scopus.citations | 5 | |
fei.scopus.eid | 2-s2.0-85098997001 | |
fei.scopus.subject | Evolutionary approach | |
fei.scopus.subject | Interactive approach | |
fei.scopus.subject | Interactive optimization | |
fei.scopus.subject | Knowledge and experience | |
fei.scopus.subject | Monte carlo analysis | |
fei.scopus.subject | Optimization tools | |
fei.scopus.subject | Radio frequency circuit | |
fei.scopus.subject | Wireless communications | |
fei.scopus.updated | 2025-02-01 | |
fei.scopus.url | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85098997001&origin=inward |