基于支撑集融合的分布式协作压缩频谱检测方法

针对认知无线电(cognitive radio, CR)宽带频谱检测过程中存在的采样压力大、数据传输量大、信道衰落严重等问题,提出了一种基于支撑集融合的分布式协作压缩频谱检测方法。在该方法中,本地信号重构过程和频谱稀疏支撑集的分布式融合过程反复交替进行,将本地重构过程中获得的稀疏支撑集信息进行分布式融合,又将融合结果作为先验信息指导本地信号再次重构,多次重复以实现信号重构与频谱检测。仿真结果表明,所提出方法的频谱检测性能可接近集中式的压缩检测方法,而该方法的迭代重构过程复杂度低,具有计算开销少的优势。

Distributed cooperative compressed spectrum sensing scheme based on support set fusion

In the cognitive radio system, a distributed cooperative compressed spectrum sensing scheme based on support set fusion is proposed in order to solve the problems of wideband spectrum detection, i.e., high sampling pressure, huge data transmission overheads and serious channel fading. In this scheme, the local reconstruction process of compressed signals and the distributed fusion process of support sets are alternately carried out. On the one hand, the support set information obtained in the local reconstruction process is fused in a distributed manner, and on the other hand, the fusion result is used as priori information to guide the local reconstruction. Simulation results show that the spectrum detection performance of the proposed scheme is close to that of the centralized compressed detection scheme, and also this scheme has the advantage of low computational overhead due to low complexity of iterative signal recovery.