基于能量检测与Sevcik分形维数的协作频谱感知算法

在认知无线网络中，针对单节点频谱感知易受到噪声不确定性的影响和传统的能量检测法在高噪声功率场景中检测性能较差等问题，根据Sevcik分形维数(Sevcik fractal dimension, SFD)对噪声不敏感、能够区分信号与噪声波形的特点，提出一种将自适应门限的能量检测法与SFD相结合的协作频谱感知方法.通过能量检测法对接收信号进行检测判决，然后由SFD对判定为主用户不存在的信号进行复检，并将所有检测结果进行K秩融合，根据融合结果得出最终判决.仿真结果表明，本文提出的频谱感知方法对噪声不敏感，在低信噪比下的检测性能得到显著提高.

Cooperative spectrum sensing algorithm based on improved energy detection and Sevcik fractal dimension

In cognitive radio networks, the single-node spectrum sensing is susceptible to noise uncertainty, and the traditional energy detection method has poor detection performance in high noise power scenarios. As the Sevcik fractal dimension(SFD) is insensitive to noise and can distinguish signal from noise waveform, a cooperative spectrum sensing (CSS) method based on energy detection and SFD is proposed by combining adaptive threshold energy detection method SFD method. Firstly, the received signal is detected and judged by energy detection method, and then the signal that primary user (PU) does not exist is rechecked by SFD. Finally, all the detection results are fused by K-out-of-N rule, and final decision is obtained according to fusion result. Simulation results show that the proposed spectrum sensing method is insensitive to noise, and the detection performance is significantly improved at low signal-noise-rate (SNR).