基于B-Spline神经网络的宽带通信发射机指纹估计

doi:10.3969/j.issn.0255-8297.2019.01.002

应用科学学报 ›› 2019, Vol. 37 ›› Issue (1): 12-23.doi: 10.3969/j.issn.0255-8297.2019.01.002

基于B-Spline神经网络的宽带通信发射机指纹估计

袁红林, 陆小丹, 徐晨

南通大学电子信息学院, 江苏南通 226019

收稿日期:2018-05-07 修回日期:2018-10-17 出版日期:2019-01-31 发布日期:2019-01-31
通信作者: 袁红林,博士,副教授,研究方向:通信设备硬件指纹认证等,E-mail:yuan.hl@ntu.edu.cn E-mail:yuan.hl@ntu.edu.cn

Estimation of Broadband Communication Transmitter Fingerprints Based on B-Spline Neural Network

YUAN Hong-lin, LU Xiao-dan, XU Chen

School of Electronics and Information, Nantong University, Nantong 226019, Jiangsu Province, China

Received:2018-05-07 Revised:2018-10-17 Online:2019-01-31 Published:2019-01-31

摘要/Abstract

摘要：

提出了一种根据接收正交频分复用（orthogonal frequency division multiplexing，OFDM）信号估计发射机IQ不平衡与非线性，并以此作为发射机指纹进行通信设备身份认证的方法.首先根据共轭对称导频估计多径信道脉冲响应，接着根据信道脉冲响应估计、共轭反对称导频与非线性功放的线性近似放大倍数估计发射机的IQ不平衡参数组合，然后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中提取相似因子，与IQ不平衡参数组合估计构成发射机指纹的特征矢量后进行通信设备身份的识别或确认.理论推导与数值仿真显示，该方法可用于OFDM通信设备的物理层高强度认证与防假冒等.

关键词: IQ不平衡, B-Spline神经网络, 通信发射机指纹, 非线性, 射频指纹, 物理层认证

Abstract:

A method for the identity authentication of orthogonal frequency division multiplexing (OFDM) communication devices with the received signal is proposed. The IQ imbalance and nonlinearity of the transmitter are estimated as the transmitter fingerprints. Firstly, the multipath channel impulse response is estimated according to the conjugate symmetric pilot. Secondly, the channel impulse response estimation, the conjugate antisymmetric pilot, and the linear approximation of the nonlinear power amplifier are used to estimate the IQ imbalance parameter combination of the transmitter. Then, the B-Spline neural network model coefficients of the nonlinearity of the transmitter are estimated. Finally, the similarity factor of the nonlinear model coefficient estimation is extracted, which constructs the feature vector of the transmitter fingerprint with the estimated IQ imbalance parameter combination. The feature vector is used to recognize or confirm the identity of the communication devices. Theoretical derivation and numerical experiments show that the proposed method can be applied to the physical layer high-intensity authentication and anti-counterfeiting of OFDM communication devices.

Key words: physical layer authentication, IQ imbalance, B-Spline neural network, communication transmitter fingerprints, radio frequency (RF) fingerprints, nonlinearity

中图分类号:

TN918.91

袁红林, 陆小丹, 徐晨. 基于B-Spline神经网络的宽带通信发射机指纹估计[J]. 应用科学学报, 2019, 37(1): 12-23.

YUAN Hong-lin, LU Xiao-dan, XU Chen. Estimation of Broadband Communication Transmitter Fingerprints Based on B-Spline Neural Network[J]. Journal of Applied Sciences, 2019, 37(1): 12-23.

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基于B-Spline神经网络的宽带通信发射机指纹估计

Estimation of Broadband Communication Transmitter Fingerprints Based on B-Spline Neural Network

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