加权随机共振多路检测的无人机频谱感知算法

UAV spectrum sensing algorithm based on weighted stochastic resonance multiplexing detection

为了提高能量检测算法在低信噪比环境下的检测性能,在广义随机共振能量检测算法的基础上,提出随机共振多路检测频谱感知算法与加权随机共振多路检测频谱感知算法。前者采用硬融合方式判决,后者定义主用户和次用户之间距离相关的权值系数,以软融合方式判决主用户占用频段的状态。仿真结果表明,当信噪比为-20 dB,虚警概率为0.2时,与广义随机共振能量检测算法和传统能量检测法相比,随机共振多路检测频谱感知算法的检测概率分别提高了5%和35%,加权随机共振多路检测频谱感知算法的检测概率分别提高了10%和45%,对微弱信号的检测性能均得到提高。

In order to improve the detection performance of energy detection algorithm in low SNR environment,a stochastic resonance multiplexing detection spectrum sensing algorithm and a weighted stochastic resonance multiplexing detection spectrum sensing algorithm are proposed,which are based on generalized stochastic resonance energy detection algorithm.The former uses hard fusion decision,while the latter defines the weight coefficient related to the distance between primary user and secondary user,and determines whether the primary user occupies the frequency band by soft fusion.The simulation results show that when the SNR is-20 dB and the false alarm probability is 0.2;compared with the generalized stochastic resonance energy detection algorithm and the traditional energy detection method,the detection probability of the stochastic resonance multiplexing detection spectrum sensing algorithm are increased by 5%and 35%respectively,and the detection probability of the weighted stochastic resonance multiplexing detection spectrum sensing algorithm are increased by 10%and 45%respectively.The detection performance of the weak signal is improved.