一种基于时频相关性的快速频谱感知算法

频谱感知技术是认知无线电的核心和基础,而自从认知无线电技术被提出以来就一直受到极大的关注。通过对无线频谱占用情况的实时采集处理,对频谱占用情况在时域和频域上的相关性进行分析。利用这种时频域的相关性提出一种快速频谱感知算法,通过频繁模式挖掘提取有效模式,使得在只需要对部分频域和时域的频谱进行检测,就可以完成对整个频谱的占用情况的认知。最后通过实时采集数据进行实验分析,表明该算法确实能达到较好的性能。

A Fast Spectrum Sensing Algorithm based on Time-Frequency Correlation

Spectrum sensing technology is the core and foundation of cognitive radio, and cognitive radio always attracts great attention since its presence. Through the real-time acquisition and processing of wireless spectrum occupation, the correlation of spectrum utilization both in time domain and frequency domain is analyzed. Based on this time-frequency domain correlation, a fast spectrum sensing algorithm is proposed. Through frequent pattern mining and extracting effective model,and only by detecting the frequency spectrum of partial frequency-domain and time-domain, this algorithm could realize cognition of the whole channel state. Finally, experimental analysis based on real-time data collection indicate that this algorithm could achieve fairly good performance.