中文摘要：

认知无线电（CR）的核心是认知引擎设计。为适合变化的无线环境状况,提出了一种基于最小二乘支持向量机的认知无线电认知引擎设计方法,该引擎根据经验知识,动态重配置无线环境参数。在802.11a仿真平台上模拟认知无线电通信系统模型,通过样本值训练支持向量机的分类、回归模型,并利用该模型学习信道特征,建立相应的认知引擎。在对感知信息进行学习前提下,实现满足用户需求的无线通信参数配置功能。仿真结果表明,该认知引擎能有效地实现认知无线电学习重构功能。

英文摘要：

Cognitive radio（CR） is an intelligent wireless communication system,and its core is to design cognitive engine.This paper presents a design scheme for cognitive engine based on least squares support vector Machine（LS-SVM） to adapt varied wireless environment according to experiential knowledge.A CR simulation cognitive engine is realized on 802.11a simulation platform by collecting data and training the classification and regression model of LS-SVM to learn channel characteristics.Under the premise of studying the sensaed information,a CR reconfiguration is realized according to the user＇s needs.The simulation results show that the proposed cognitive engine can effectively realize the learning and reconfiguration function.