基于压缩感知理论的宽带多用户认知系统合作检测

Compressed sensing based multi-user collaborative detection for wideband cognitive radio networks

利用信道相关估计、压缩采样以及基追踪的信号重构理论,并应用平均一致算法实现了多用户合作检测。在瑞利衰落信道环境中,将本文算法与传统能量检测算法进行了仿真比较。仿真结果表明:与传统能量检测算法相比,本文算法在较低信噪比环境中,使用较少的采样数量即可获得较好的检测性能;同时,当认知用户增加时,检测性能也有所提高。

Using correlated channel estimation, compressive sampling theory, signal reconstruction based on the basis pursuit technique and the average-consensus algorithm, the proposed algorithm realizes effective and accurate signal detection. The proposed algorithm is compared with the traditional energy detection scheme in the condition of Rayleigh fading. Results show that the proposed algorithm can achieve better performance than the energy detection scheme in low SNR and less sampling rate scenario. Meanwhile, the detection performance can also be improved when the cognitive radio users increase.