基于频域复杂度分析的频谱感知算法

摘要

A spectrum sensing algorithm based on LZC analysis in spectral domain was proposed.CR users transform the received signal into spectral sequences.Then the sequences are analyzed by LZC method so as to distinguish noise from signal and decide the activity of PU.This algorithm promotes the detection probability under low SNR.Simulation result show that the proposed method resists to SNR uncertainty and improves the sensing performance in cognitive radio networks.%提出了在频域范围内基于复杂度分析的频谱感知算法,次用户首先将接收到的信号变换到频域,然后,对变换后的频域信号进行Lempel-Ziv复杂度分析,区分出噪声和有用信号,从而确定主用户是否活跃.该方法在信噪比很低的情况下也具有较高的检测概率.仿真结果表明,该方法对噪声抵抗性很强,能显著改善认知无线网络频谱感知的能力.