Open AccessCognitive radio resource allocation based on combined chaotic genetic algorithm
Author(s) -
Yunxiao Zu,
Jie Zhou
Publication year - 2011
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.60.079501
Subject(s) - chaotic , cognitive radio , computer science , algorithm , genetic algorithm , resource allocation , rate of convergence , mathematical optimization , simulated annealing , transmission (telecommunications) , convergence (economics) , machine learning , artificial intelligence , wireless , mathematics , computer network , telecommunications , channel (broadcasting) , economics , economic growth
The combined chaotic genetic algorithm for cognitive radio resource allocation is proposed, and corresponding combined chaotic sequence generator is designed. Simulations are conducted by using the combined chaotic genetic algorithm, the particle swarm optimization algorithm, the simulated annealing algorithm, and the simple genetic algorithm, thereby analyzing the multi-users, cognitive radio resource allocation. The results show that the combined chaotic genetic algorithm has advantages of fast convergence rate, vast search space and global convergence. The combined chaotic genetic algorithm has better performance than the other three algorithms in terms of cognitive radio resource allocation, there by reducing the bit error rate and the transmission power consumption of the system. Besides, it also has a faster convergence rate.