• DocumentCode
    1733030
  • Title

    Optimizing CMOS LNA circuits through multi-objective meta heuristics

  • Author

    Kotti, Mouna ; Sallem, Amin ; Bougharriou, Mariam ; Fakhfakh, Mourad ; Loulou, Mourad

  • Author_Institution
    Univ. of Sfax, Sfax, Tunisia
  • fYear
    2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Particle swarm optimization (PSO) has shown to be an efficient, robust and simple optimization algorithm. Recently, the mono-objective version of the PSO algorithm was adapted and used to optimize only one performance of RF circuits, mainly the voltage gain of low noise amplifiers. In this work, we propose to optimize more than one performance function of LNAs while satisfying imposed and inherent constraints. We deal with generating the Pareto front linking two conflicting performances of a LNA, namely the voltage gain and the noise figure. The adopted idea consists of using the symbolic expressions of the scattering parameters ((S21) for the voltage gain, and (S11, S22) for input and output matching). For this purpose we use a Multi-Objective Optimization algorithm PSO incorporating the mechanism of the crowding distance technique (MOPSO-CD). Comparisons with results obtained using NSGA II are presented and ADS simulations, using 0.35μm CMOS technology, are given to show good reached results.
  • Keywords
    CMOS analogue integrated circuits; low noise amplifiers; particle swarm optimisation; ADS simulations; CMOS LNA circuits; CMOS technology; NSGA II; PSO; RF circuits; low noise amplifiers; multi-objective meta heuristics; noise figure; particle swarm optimization; scattering parameters; size 0.35 mum; voltage gain; Algorithm design and analysis; Impedance matching; Integrated circuit modeling; Noise figure; Optimization; Scattering parameters;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Symbolic and Numerical Methods, Modeling and Applications to Circuit Design (SM2ACD), 2010 XIth International Workshop on
  • Conference_Location
    Gammath
  • Print_ISBN
    978-1-4244-6816-4
  • Type

    conf

  • DOI
    10.1109/SM2ACD.2010.5672305
  • Filename
    5672305