基于盒子维数和最大Lyapunov维数的瞬态信号特征提取

Transient signal feature extraction based on box dimension and maximum Lyapunov dimension

认知无线电是一种通过无线频谱感知来有效提高频谱利用率的无线通信技术。它除了面临传统无线通信的各种安全问题外,还会面临一些新的问题,比如模仿主用户攻击(PUE)。提出基于分形维数的瞬态信号特征提取来预防认知无线网络中的模仿主用户攻击,并通过实验提取无线发射机的分形维数,为下一步信号识别提供可靠的特征参数,达到预防PUE攻击的目的。

Cognitive radio is one kind of wireless communication technology, which effectively improves the spectrum efficiency by the way of wireless spectrum sensing. Besides of varieties of security issues of the traditional wireless communication, it also has some new problems, such as Primary User Emulation （PUE） attack. This paper proposes that the transient signal characteristics extraction based on the fractal dimension protects the PUE attack from the cognitive wireless networks, and then extracts the fractal dimension of wireless transmitter through experiments, which provides reliable characteristic parameters for the next signal recognition to prevent the attack of PUE.