基于循环平稳的图样特征识别频谱检测方法  

Pattern recognition spectrum detection method based on cyclostationarity

作　　者：王尚[1] 汪一鸣[1] 欧扬[2] 

机构地区：[1]苏州大学电子信息学院,江苏苏州215021 [2]苏州科技学院电子信息学院,江苏苏州215011

出　　处：《计算机工程与应用》2013年第11期153-157,共5页Computer Engineering and Applications

基　　金：国家自然科学基金项目(No.60872003);苏州市应用基础研究计划项目(No.SYJG0925);博士学科点专项科研基金(No.20093201110005)

摘　　要：频谱空穴检测是认知无线电研究的关键技术。针对认知无线电系统中甚低信噪比环境下频谱检测的困难,基于循环平稳理论,提出对接收信号的循环谱密度函数俯视图特殊图样的模式识别来进行频谱检测判决的方法。由此设计出谱峰搜索检测与图样特征识别相结合的频谱检测判决机制。实验仿真结果表明,所提出的检测方法性能良好,可以有效地对弱主用户信号进行频谱检测。Spectrum hole detection is the key technology of cognitive radio. For the difficulties of spectrum detection in lower SNR, a new spectrum detection method based on cyclostationary theory is proposed. This method is to carry out pattern recogni- tion on the unique planforrn of the received signals＇ cyclostationary spectral density function. And the detection mechanism using peak searching combined with pattern recognition is designed. Simulation results show that, the detection performance of the proposed method is better than that of peak searching. And it can detect the weak primary users＇ signals effectively.

关 键 词：认知无线电 频谱检测 循环平稳 俯视图 

分 类 号：TN911[电子电信—通信与信息系统]