Open AccessCognitive radio decision engine based on binary particle swarm optimization
Author(s) -
Zhijin Zhao,
Xu Shen,
Shilian Zheng,
Xiaoniu Yang
Publication year - 2009
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.58.5118
Subject(s) - particle swarm optimization , multi swarm optimization , cognitive radio , computer science , metaheuristic , population , swarm behaviour , mathematical optimization , convergence (economics) , meta optimization , artificial intelligence , algorithm , mathematics , telecommunications , demography , sociology , economics , wireless , economic growth
Cognitive radio decision engine based on particle swarm optimization is proposed. A population adaptive particle swarm optimization is also proposed to improve the convergence rate. Particle swarm optimization and population adaptive particle swarm optimization are used to adapt radio parameters respectively, and multi-carrier system is used for the performance analysis. Results show that cognitive decision engine based on binary particle swarm optimization has better convergence, precision and stability than the classic genetic algorithm, and population adaptive particle swarm optimization can further improve the performance at the initial stage of the search to meet real time requirement of cognitive radio.