认知无线电差分协作压缩频谱估计算法

在分布式认知无线网络场景下，针对传统协作压缩频谱估计收敛速度慢、计算复杂度高的问题，提出了一种差分协作压缩频谱估计算法用于宽带频谱感知。算法通过利用不同认知用户感知的宽带信号所满足的相同频谱支撑集特征，实现了在邻居节点感知先验信息条件下，本地认知用户基于压缩测量向量差值的宽带频谱迭代估计。仿真分析结果表明，所提算法在频谱估计精度、检测性能与计算复杂度方面均获得了明显改善。

Differential cooperative compressed spectrum estimation for cognitive radio

In distributed cognitive radio network (CRN) scenario, this paper proposes a differential cooperative compressed spectrum estimation(DCCSE) algorithm for wide band sensing, which can address the problems like slow convergence rate and high complexity encountered by traditional schemes effectively. Since the wide band signals sensed by different cognitive users share the common spectrum support set, DCCSE can estimate the wide band spectrum iteratively based on the difference of the compressed sensing(CS) measurements, with the help of the priori sensing information provided by neighboring users. Simulation results validate the marked improvements of the presented algorithm in spectrum estimation precision, detection performance and computational complexity.