Cognitive Radio Adaptation Decision Engine Based on Binary Quantum-Behaved Particle Swarm Optimization

被引：0

作者：

Zhang, Jing ^{[1
,2
]}

Zhou, Zheng ^{[1
]}

Gao, Wanxin ^{[1
]}

Ma, Yingjie ^{[1
]}

Ye, Yabin ^{[3
]}

机构：

[1] Beijing Univ Posts & Telecommun, Key Lab Universal Wireless Commun, MOE Wireless Network Lab, Beijing 100088, Peoples R China

[2] 54th Res Inst CETC, Shijiazhuang, Hebei, Peoples R China

[3] Huawei Technol Duesseldorf GmbH, European Res Ctr, Louvain, Belgium

来源：

2011 6TH INTERNATIONAL ICST CONFERENCE ON COMMUNICATIONS AND NETWORKING IN CHINA (CHINACOM) | 2011年

关键词：

Cognitive Radio; decision engine; convergence speed; OFDM; PSO; BPSO; BQPSO;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：221 / 225

页数：5

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