认知网络中多速率采样的宽带合作频谱感知

Wideband Cooperative Spectrum Sensing of Multi-rate Sampling in Cognitive Radio Networks

在合作感知的框架下,提出一种基于多速率sub-Nyquist采样(Co-MRSS)的宽带合作频谱感知算法。认知无线电网络中每个合作节点首先以不同的sub-Nyquist速率对信号进行采样,然后将各自的采样信息集中到融合中心(FC),利用压缩感知CoSaMP重构算法来重构信号的频谱幅度,最后将重构的频谱幅度其能量值与设定的门限值作比较,来判断主用户(PU)是否存在。Co-MRSS有效地减少了信号采样的数量,降低了计算复杂度。进行了仿真实验以验证算法的有效性。

A wideband cooperative spectrum sensing algorithm based on multi-rate sub-Nyquist sampling （Co-MRSS） was developed. Firstly, the signal was sampled in different sub-Nyquist rates by each cooperative node in cognitive radio network, then sampling information of each cooperative node was sent to the fusion central （FC）, spectrum amplitude of the signal was reconstructed by CoSaMP algorithm and energy of the reconstructed spectrum amplitude was calculated. Finally, the energy was compared with a preset detection threshold to decide whether the primary user （PU） is existed. The number of signal samples and computational complexity was reduced effectively by the Co-MRSS. Effects of the proposed system are demonstrated by simulations.