Title :
Immune genetic algorithm-based parameters optimization of cognitive radios
Author_Institution :
Sch. of Inf. Sci. & Tech., Zhe Jiang Forestry Univ., Hangzhou, China
Abstract :
Genetic algorithms are best suited for optimization problems. But premature convergence exists when genetic algorithm applied for optimization problems. The immune genetic algorithm (IGA) combined artificial immune system and GA together is presented to overcome this problem. Finally, the IGA is used to solve parameter optimization problems of cognitive radios. Simulation results demonstrate that IGA can rapidly reach an optimal decision.
Keywords :
artificial immune systems; cognitive radio; convergence; genetic algorithms; artificial immune system; cognitive radio; immune genetic algorithm; parameter optimization problem; premature convergence; Artificial immune system; Cognitive radios; Genetic algorithms; Multi-objective optimization;
Conference_Titel :
Microwave Technology and Computational Electromagnetics, 2009. ICMTCE. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-84919-140-1
DOI :
10.1049/cp.2009.1369
