循环功率谱特征检测算法在认知超宽带无线通信的应用
doi: 10.3724/SP.J.1146.2007.00495
Application of Cyclic Spectrum Feature Detection to Cognitive UWB Wireless Communication
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摘要: 认知超宽带无线通信技术结合了超宽带无线通信技术和认知无线电技术，信号频谱检测是认知超宽带无线通信系统的核心模块之一。循环平稳特性普遍存在于各种调制信号中，该文研究了一种新的检测算法循环功率谱特征检测算法，并以OFDM信号为例给出了软件仿真和性能分析。该检测算法能够区分有用信号，噪声信号和干扰信号，是最适合认知超宽带无线通信系统的。Abstract: Cognitive UWB technology combines UWB technology and Cognitive Radio (CR) technology. Spectrum detection is one of key modules for Cognitive UWB wireless communication system. Cyclostationary characteristic is ubiquitous in almost all the modulated signals. This paper investigates a new detection method that is Cyclic Spectrum Feature Detection (CSFD). Setting OFDM signal as example, it gives out the software simulation and performance analysis. This Detection method can distinguishes desired signal, noise and interference signal, so it is optical for Cognitive UWB wireless communication system.
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