摘要： 在认知无线电网络的主用户动态到达频谱感知场景中，针对拉普拉斯脉冲噪声干扰导致频谱检测性能下降的问题，提出基于绝对值累积（AVC）的频谱感知算法。假设接收到的主用户信号服从泊松分布，对接收信号进行AVC处理抑制脉冲噪声干扰，并将处理信号累积求和作为判决统计量，得到判决统计量的均值与方差，求出判决门限理论表达式以判断主用户是否动态到达，从而实现频谱感知。理论分析与仿真结果表明，该算法在不同虚警概率、信噪比及累积求和采样点数量下的检测概率均优于改进的能量检测算法。

关键词: 认知无线电网络, 拉普拉斯噪声, 能量检测, 绝对值累积, 主用户

Abstract: The spectrum sensing scene with dynamic arrivals of Primary User(PU) in Cognitive Radio Network(CRN) often suffers from Laplace impulse noise,which leads to a drop in spectrum sensing performance.To address this problem,this paper proposes a spectrum sensing algorithm based on Absolute Value Cumulation(AVC).The algorithm assumes that received PU signals follow the Poisson distribution,and performs AVC on received signals to reduce interference of impulse noise.The accumulated sum of processed signals serves as the decisive statistics,and the mean value and variance of the decisive statistics are obtained.On this basis,the expression of decision threshold theory can be derived to judge whether the PU dynamically arrives,so as to implement spectrum sensing.Theoretical analysis and simulation results show that the proposed algorithm achieves a higher detection probability than the Improved Energy Detection(IED) algorithm under different false alarm probabilities,signal to noise ratio and sampling points.

Key words: Cognitive Radio Network(CRN), Laplace noise, Energy Detection(ED), Absolute Value Cumulation(AVC), Primary User(PU)

中图分类号: 

• TN925