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基于近似解的单载波通信发射机指纹估计

Estimation of Single-Carrier Communication Transmitter Fingerprints Based on Approximate Solution

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【作者】 袁红林赵晏严燕杨永杰

【Author】 YUAN Honglin;ZHAO Yan;YAN Yan;YANG Yongjie;School of Electronics and Information, Nantong University;School of Computer Science and Technology, Nantong University;

【机构】 南通大学电子信息学院南通大学计算机科学与技术学院

【摘要】 提出了一种单载波块传输通信中的发射机IQ不平衡与非线性指纹估计方法.新方法基于由分别加循环前缀的纯实数与纯虚数子块构成的通信帧.首先根据纯实数子块估计多径信道道脉冲响应,接着根据发射机功放的线性近似放大倍数、信道脉冲响应估计与纯虚数子块进行发射机的IQ不平衡参数组合估计,然后根据信道脉冲响应及IQ不平衡参数组合估计进行发射机非线性的B-Spline神经网络模型系数估计,最后从非线性模型系数估计提取相似因子特征,与IQ不平衡参数组合估计构成发射机指纹的特征矢量,用于通信设备身份的识别或确认.理论推导与数值仿真实验结果表明,提出的IQ不平衡及非线性指纹方法可应用于单载波合作通信设备的跨层高强度硬件认证与防假冒等.

【Abstract】 An estimation method of IQ imbalance and nonlinear fingerprints of communication transmitters in single-carrier block transmission is proposed. The novel method is based on a kind of communication frame, which consists of a pure real number and a pure imaginary number sub-block added with cyclic prefix respectively. Firstly, the multipath channel impulse response is estimated with the pure real number sub-block. Then, according to the linear approximation amplification of the transmitter power amplifier, the channel impulse response estimation and the pure imaginary number sub-block, the IQ imbalance parameter combination is estimated, and then the channel impulse response and the IQ imbalance parameter combination estimation are used to estimate the coefficient of the B-Spline neural network model of the transmitter nonlinearity. Finally, the resemblance coefficient feature is extracted from the estimated nonlinear coefficients, which is assembled with the IQ imbalance estimation to form the feature vector of the transmitter fingerprints. And the feature vector is used to identify or recognize the communication devices. It is shown by theoretical derivation and numerical simulations that the proposed method can be applied for the cross-layer high-strength authentication and anti-counterfeiting of single-carrier co-operational communication devices.

【基金】 南通大学教学改革研究课题(2017B38)
  • 【文献出处】 南通大学学报(自然科学版) ,Journal of Nantong University(Natural Science Edition) , 编辑部邮箱 ,2018年04期
  • 【分类号】TN913.6
  • 【下载频次】54
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