A bio-inspired approach for cognitive radio networks  

作　　者：HE ZhiQiang NIU Kai QIU Tao SONG Tao XU WenJun GUO Li LIN JiaRu 

机构地区：[1]Key Laboratoty of Universal Wireless Communications,Ministry of Education,Beijing University of Posts and Telecommunications,Beijing 100876,China

出　　处：《Chinese Science Bulletin》2012年第28期3723-3730,共8页

基　　金：supported by the National Basic Research Program of China (2009CB320401);Major Projects of the National Science and Technology of China (2012ZX03004005-002);National Natural Science Foundation of China (61171100 and 61171099)

摘　　要：The recent increasing interest in cognitive radio networks has motivated the study and development of new approaches capable of coping with the intrinsic challenges of this kind of network,such as dynamic spectrum availability,distributed and heterogeneous network architectures,and soaring complexity.The bio-inspired approaches,with appealing characteristics such as autonomy,adaptation and collective intelligence of collaborative individuals,have been extensively studied.This paper presents a comprehensive survey of bio-inspired approaches for cognitive radio networks,emphasizing their domains of application.Specifically,ant colony optimization and particle warm optimization are further investigated with examples and numerical simulation.The recent increasing interest in cognitive radio networks has motivated the study and development of new approaches capable of coping with the intrinsic challenges of this kind of network, such as dynamic spectrum availability, distributed and heterogeneous network architectures, and soaring complexity. The bio-inspired approaches, with appealing characteristics such as autonomy, adaptation and collective intelligence of collaborative individuals, have been extensively studied. This paper presents a compre- hensive survey of bio-inspired approaches for cognitive radio networks, emphasizing their domains of application. Specifically, ant colony optimization and particle warm optimization are further investigated with examples and numerical simulation.

关 键 词：无线电网络 仿生 网络架构 综合调查 数值模拟 蚁群算法 可用性 复杂性 

分 类 号：TN929.5[电子电信—通信与信息系统] TB39[电子电信—信息与通信工程]