Cognitive Radio Engine Design Based on Ant Colony Optimization

被引：40

作者：

Zhao, Nan ^{[1
]}

Li, Shuying ^{[2
]}

Wu, Zhilu ^{[2
]}

机构：

[1] Dalian Univ Technol, Sch Informat & Telecommun Engn, Dalian 116024, Liaoning, Peoples R China

[2] Harbin Inst Technol, Sch Elect & Informat Technol, Harbin 50001, Heilongjiang, Peoples R China

来源：

WIRELESS PERSONAL COMMUNICATIONS | 2012年 / 65卷 / 01期

关键词：

Cognitive radio; Decision engine; Ant colony optimization; Mutation mechanism; Genetic algorithm; ALGORITHM;

D O I：

10.1007/s11277-011-0225-7

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

In this letter, a mutated ant colony optimization (MACO) cognitive radio engine is proposed, and it is the first time to apply ACO algorithm to this problem. The cognitive radio is a promising technology nowadays to alleviate the apparent scarcity of available radio spectrum, and the cognitive radio engine determines the optimal radio transmission parameters for the system. The cognitive engine problem is usually solved by genetic algorithm (GA), however, the GA converges slowly and its performance can still be improved. Hence, MACO algorithm with excellent performance is applied to the cognitive engine in this letter. Simulation results show that the fitness scores obtained by the MACO engine are much better than the ACO and GA engines in different scenarios.

引用

页码：15 / 24

页数：10

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