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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Optimization of a low noise amplifier with two technology nodes using an interactive evolutionary approach

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Autor(es):
de Lima Moreto, Rodrigo Alves [1] ; Mariano, Andre [2] ; Thomaz, Carlos Eduardo [1] ; Gimenez, Salvador Pinillos [1]
Número total de Autores: 4
Afiliação do(s) autor(es):
[1] FEI Univ Ctr, Dept Elect Engn, Av Humberto Alencar Castelo Branco 3972, BR-09850901 Sao Bernardo Do Campo, SP - Brazil
[2] Univ Parana, Dept Elect Engn, Curitiba, Parana - Brazil
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: ANALOG INTEGRATED CIRCUITS AND SIGNAL PROCESSING; v. 106, n. 1, p. 307-319, JAN 2021.
Citações Web of Science: 0
Resumo

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. (AU)

Processo FAPESP: 18/21341-4 - Protótipo de inteligência computacional interativa para projeto e otimização de circuitos integrados analógicos
Beneficiário:Rodrigo Alves de Lima Moreto
Modalidade de apoio: Auxílio à Pesquisa - Pesquisa Inovativa em Pequenas Empresas - PIPE