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
Link To Document :
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