Open AccessCognitive radio adaptation using particle swarm optimization
Author(s) -
Zhao Zhijin,
Xu Shiyu,
Zheng Shilian,
Shang Junna
Publication year - 2009
Publication title -
wireless communications and mobile computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.42
H-Index - 64
eISSN - 1530-8677
pISSN - 1530-8669
DOI - 10.1002/wcm.633
Subject(s) - computer science , cognitive radio , particle swarm optimization , adaptation (eye) , stability (learning theory) , convergence (economics) , set (abstract data type) , genetic algorithm , fitness function , mathematical optimization , algorithm , machine learning , telecommunications , mathematics , physics , optics , wireless , economics , programming language , economic growth
One of the basic capabilities of cognitive radio is to adapt the radio parameters according to the changing environment and user needs. This paper proposes a new adaptation method which uses particle swarm optimization (PSO) to optimize cognitive radio parameters given a set of objectives. The procedure of the proposed method is presented and multicarrier system is used for simulation analysis. Experimental results show that the proposed method performs far better than genetic algorithm (GA)‐based adaptation method in terms of convergence speed, converged fitness values, and stability. The proposed method can also provide the tradeoffs of the objective functions, and the resulting parameter configuration is consistent with the weights of the objective functions. Copyright © 2008 John Wiley & Sons, Ltd.