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. They are implemented by Radio Frequency (RF) circuits. However, the design of RF circuits is difficult, time-consuming and based on designer knowledge and experience. This work proposes an interactive evolutionary approach using the genetic algorithm, which is implemented in the in-house iMTGSPICE optimization tool, to perform the optimization process of a robust (corner and Monte Carlo analyses) Ultra Low-Power Low Noise Amplifier (LNA) dedicated to Wireless Sensor Networks (WSN), which is implemented in a 130 nm Bulk CMOS technology. We performed two experimental studies to optimize the LNA. The first one used the interactive approach of iMTGSPICE, which was monitored and assisted by a beginner designer during the optimization process. The second one used the conventional approach of iMTGSPICE (non-interactive), which was not assisted by a designer during the optimization process. The obtained results demonstrated that the interactive approach of iMTGSPICE performed the optimization process of the robust LNA around 94% faster (in approximately 20 minutes only) than the non-interactive evolutionary approach (in approximately 6 hours).

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Wang YPei Y(2024)A comprehensive survey on interactive evolutionary computation in the first two decades of the 21st centuryApplied Soft Computing10.1016/j.asoc.2024.111950164(111950)Online publication date: Oct-2024
https://doi.org/10.1016/j.asoc.2024.111950
de Lima Moreto RMariano AThomaz CGimenez S(2021)Optimization of a low noise amplifier with two technology nodes using an interactive evolutionary approachAnalog Integrated Circuits and Signal Processing10.1007/s10470-020-01755-1Online publication date: 2-Jan-2021
https://doi.org/10.1007/s10470-020-01755-1

Index Terms

Interactive evolutionary approach to reduce the optimization cycle time of a low noise amplifier
1. Computing methodologies
  1. Artificial intelligence
2. Hardware
  1. Electronic design automation
    1. Methodologies for EDA
      1. Software tools for EDA

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SBCCI '19: Proceedings of the 32nd Symposium on Integrated Circuits and Systems Design

August 2019

204 pages

ISBN:9781450368445

DOI:10.1145/3338852

General Chair:
João Martino
USP, Brazil
,
Program Chairs:
Marcelo Lubaszewski
UFRGS, Brazil
,
Matteo Reorda
Politec. di Torino, Italy

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Published: 26 August 2019

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SBCCI '19: 32nd Symposium on Integrated Circuits and Systems Design

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Wang YPei Y(2024)A comprehensive survey on interactive evolutionary computation in the first two decades of the 21st centuryApplied Soft Computing10.1016/j.asoc.2024.111950164(111950)Online publication date: Oct-2024
https://doi.org/10.1016/j.asoc.2024.111950
de Lima Moreto RMariano AThomaz CGimenez S(2021)Optimization of a low noise amplifier with two technology nodes using an interactive evolutionary approachAnalog Integrated Circuits and Signal Processing10.1007/s10470-020-01755-1Online publication date: 2-Jan-2021
https://doi.org/10.1007/s10470-020-01755-1

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

A broadband Low Noise Amplifier with built-in linearizer in 0.13-µm CMOS process

An Inductor-less Sub-mW Low Noise Amplifier for Wireless Sensor Network Applications

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