一种低速采样的协同宽带频谱感知方法

A Cooperative Spectrum Sensing Method Based on Low Rates Sampling

频谱感知是通信系统抗干扰和智能化的关键能力。针对认知无线电系统窄带频谱感知技术受制于数模转换器件的发展水平,难以解决认知无线电系统宽带、实时频谱感知的问题,提出一种多节点协作的认知无线电系统宽带频谱感知方法。该方法设计由多个认知节点对目标频段执行次奈奎斯特采样来降低采样速率,采用能量检测方式对采样矢量进行集中式融合判决,实现宽频段范围内干扰信号的谱定位和判断,降低各个感知节点的采样速率,支撑认知网络系统构建高实时、宽频带频谱感知的能力。计算机仿真试验结果表明,所提方法达到90%检测概率时压缩比要求为0.025,具有可靠性与有效性。

Spectrum sensing is a key capability to enhance the anti-jamming and intelligence level of a communication system. The narrowband spectrum sensing performance of cognitive radio system is restricted by the technological progress of the analog digital converter, so it is difficult to realize the high real-time performance and wideband detection in system. In response to the problem, a method is proposed based on cooperative wideband spectrum sensing between multi-cognitive nodes in the network. In order to achieve high real-time performance and wideband detection of cognitive network system, the method reduces the sampling rate by making cognitive nodes perform sub-Nyquist sampling on the sensing frequency band, and realizes the positioning and judgment of jamming signal in the wide range of frequency through the central-ized fusion and decision mechanism based on energy detection. The simulation and experimental results show that the proposed method can achieve 90% detection probability under the condition that compression ratio is 0. 025. So the method is correct and reliable.