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
收藏
页码：15 / 24
页数：10
相关论文
共 50 条
  • [1] Cognitive Radio Engine Design Based on Ant Colony Optimization
    Nan Zhao
    Shuying Li
    Zhilu Wu
    Wireless Personal Communications, 2012, 65 : 15 - 24
  • [2] Reconfiguration Decision Making Based on Ant Colony Optimization in Cognitive Radio Network
    Qian He
    Zhiyong Feng
    Ping Zhang
    Wireless Personal Communications, 2013, 71 : 1247 - 1269
  • [3] Reconfiguration Decision Making Based on Ant Colony Optimization in Cognitive Radio Network
    He, Qian
    Feng, Zhiyong
    Zhang, Ping
    WIRELESS PERSONAL COMMUNICATIONS, 2013, 71 (02) : 1247 - 1269
  • [4] Topology Reconfiguration in Cognitive Radio Networks using Ant Colony Optimization
    Zhang, Qixun
    He, Qian
    Zhang, Ping
    2012 IEEE VEHICULAR TECHNOLOGY CONFERENCE (VTC FALL), 2012,
  • [5] Dynamic Channel Assignment using Ant Colony Optimization for Cognitive Radio Networks
    He, Qian
    Zhang, Ping
    2012 IEEE VEHICULAR TECHNOLOGY CONFERENCE (VTC FALL), 2012,
  • [6] Design optimization based on neural networks and ant colony optimization
    Guo, Wu Yu
    Zhi, Song Chong
    ICIEA 2007: 2ND IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOLS 1-4, PROCEEDINGS, 2007, : 360 - 362
  • [7] An Extended Ant Colony based Routing Algorithm for Cognitive Radio Networks
    Hu, Qingsong
    Zhang, Shen
    Zhou, Zhongqiang
    2012 WORLD AUTOMATION CONGRESS (WAC), 2012,
  • [8] Ant colony optimization-based firewall anomaly mitigation engine
    Penmatsa, Ravi Kiran Varma
    Vatsavayi, Valli Kumari
    Samayamantula, Srinivas Kumar
    SPRINGERPLUS, 2016, 5
  • [9] Engine universal characteristic modeling based on improved ant colony optimization
    Chen Fuen
    Jiang Shihui
    Xie Xin
    Chen Longhan
    Lan Yubin
    INTERNATIONAL JOURNAL OF AGRICULTURAL AND BIOLOGICAL ENGINEERING, 2015, 8 (05) : 26 - 35
  • [10] An Improved algorithm of parameters reconfiguration in cognitive radio networks using ant colony optimization
    Liu, Shaoyuan
    Zeng, Fanzi
    Xu, Jisheng
    2015 3RD INTERNATIONAL CONFERENCE ON MANUFACTURING ENGINEERING AND TECHNOLOGY FOR MANUFACTURING GROWTH (METMG 2015), 2015, : 128 - 132
12345