Research Article
Cognitive Radio Adaptation Decision Engine Based on Binary Quantum-Behaved Particle Swarm Optimization
@INPROCEEDINGS{10.1109/ChinaCom.2011.6158152, author={zheng zhou and Jing Zhang and Wanxin Gao and Yingjie Ma and Yabin Ye}, title={Cognitive Radio Adaptation Decision Engine Based on Binary Quantum-Behaved Particle Swarm Optimization}, proceedings={6th International ICST Conference on Communications and Networking in China}, publisher={IEEE}, proceedings_a={CHINACOM}, year={2012}, month={3}, keywords={cognitive radio decision engine convergence speed ofdm pso bpso bqpso}, doi={10.1109/ChinaCom.2011.6158152} }- zheng zhou
Jing Zhang
Wanxin Gao
Yingjie Ma
Yabin Ye
Year: 2012
Cognitive Radio Adaptation Decision Engine Based on Binary Quantum-Behaved Particle Swarm Optimization
CHINACOM
IEEE
DOI: 10.1109/ChinaCom.2011.6158152
Abstract
Cognitive Radio decision engine is a key technology in cognitive communication system. It can optimize transmission parameters according to the environment, and obtain the desired communication performance through multi-objective optimization algorithm. In this paper, we analyze the Cognitive Radio decision engine based on OFDM system, and introduce a binary quantum-behaved particle swarm optimization algorithm (BQPSO), which has stronger optimal searching ability and faster convergence speed. Because quantum effect has the excellent characteristics of nonlinearity and uncertainty, it can reach better optimize performance than other optimization algorithms. Based on OFDM system, the simulation results show that BQPSO algorithm has a good performance in convergence, speed, and average fitness value. The optimization performance can greatly satisfy the demand of cognitive radio decision engine.
