WO2021139163A1 - 射频指纹提取方法、装置、无线接收机及存储介质 - Google Patents

射频指纹提取方法、装置、无线接收机及存储介质 Download PDF

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WO2021139163A1
WO2021139163A1 PCT/CN2020/110426 CN2020110426W WO2021139163A1 WO 2021139163 A1 WO2021139163 A1 WO 2021139163A1 CN 2020110426 W CN2020110426 W CN 2020110426W WO 2021139163 A1 WO2021139163 A1 WO 2021139163A1
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group
amble
signal
short
long
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PCT/CN2020/110426
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French (fr)
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胡爱群
彭林宁
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网络通信与安全紫金山实验室
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/08—Network architectures or network communication protocols for network security for authentication of entities
    • H04L63/0876—Network architectures or network communication protocols for network security for authentication of entities based on the identity of the terminal or configuration, e.g. MAC address, hardware or software configuration or device fingerprint
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/15—Correlation function computation including computation of convolution operations
    • G06F17/156—Correlation function computation including computation of convolution operations using a domain transform, e.g. Fourier transform, polynomial transform, number theoretic transform
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/26—Systems using multi-frequency codes
    • H04L27/2601—Multicarrier modulation systems
    • H04L27/2647—Arrangements specific to the receiver only
    • H04L27/2655—Synchronisation arrangements
    • H04L27/2657—Carrier synchronisation

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  • the present invention relates to the technical field of communication and information security, in particular to a radio frequency fingerprint extraction method, device, wireless receiver and storage medium.
  • Radio Frequency Fingerprint is an inherent feature of wireless transmitting equipment. It is the tiny signal distortion caused by the transmitted signal through the transmitter circuit.
  • the transmitter contains many devices such as amplifiers, filters, frequency converters, adders, oscillators, power amplifiers, antennas, etc. Due to the deviation of the manufacturing process, the characteristics of these devices cannot be completely the same, so that any transmission equipment is impossible Have exactly the same RF fingerprint.
  • RFF is a characteristic caused by the device, so it has long-term stability and uniqueness. This feature of RFF can be used to identify wireless transmitters, it can also be used to authenticate the transmitter's identity to protect communication security, and it can also be used to implement access control over the terminal in a wireless network.
  • RFF is a weak signal generated by the transmitter and parasitic on the received signal. Its generation mechanism is very complicated. The existence of radio frequency fingerprints can be observed experimentally, but it is difficult to express it in mathematics, so it is difficult to find a theoretical method to extract radio frequency fingerprints. In particular, the multipath effect of the wireless channel has a convolutional relationship with the transmitted signal, and the radio frequency fingerprint is also convolved with the transmitted signal to a certain extent.
  • channel noise is also an interference item of the radio frequency fingerprint.
  • accumulation operations such as correlation operations, and the accumulation operation will obscure the details of the radio frequency fingerprint. Therefore, it is very difficult to directly remove channel noise from the preamble of a frame of signal.
  • the received signal may be severely distorted, and it is very difficult to extract the weak RF fingerprint signal from the received signal, especially for broadband signals. Judging from the current public literature, there has not yet been a method for extracting radio frequency fingerprints that can theoretically find a real resistance to random noise and multipath effects.
  • the embodiments of the present invention provide a radio frequency fingerprint extraction method, device, wireless receiver, and storage medium to find a breakthrough in the signal frame structure of wireless communication, and use the characteristics of multiple different symbols in the signal frame preamble. Symbols are usually used to capture signal frames, correct carrier frequency offset, automatic gain control, channel estimation, and achieve precise synchronization of symbols. In the embodiment of the present invention, these preambles are used to extract radio frequency in addition to the above-mentioned functions. fingerprint.
  • the embodiment of the present invention provides a radio frequency fingerprint extraction method, including:
  • the wireless receiver takes out all the preamble signals from the received signal frame; removes the carrier frequency offset in the preamble through signal interpolation to achieve carrier synchronization; divides the preamble signal into a long preamble group and a short preamble group, and Each group consists of two signals before and after, specifically: using the local preamble signal and the interpolated received preamble signal to calculate the cross-correlation function, and accurately determine the demarcation time between the long preamble group and the short preamble group Point, and then divide the two segment signals in each group; respectively calculate the complex cross-correlation function between the two segment signals in the long amble group and the short amble group; respectively calculate the long amble group and The power spectrum of the short amble group signal; calculate the power spectrum difference between the long amble group and the short amble group signal to obtain a radio frequency fingerprint, the long amble group and the short amble group signal
  • the transmission signal contents corresponding to the short amble group symbols d1 and d2 and the long amble group symbols c1 and c2 are different.
  • the calculation of the power spectrum of the long amble group and the short amble group signal is specifically: the complex cross-correlation between the short amble group and the two segments of the signal in the long amble group Function to do Fourier transform, get
  • the method for extracting radio frequency fingerprints further includes graphically presenting the radio frequency fingerprints on a two-dimensional plane.
  • the receiving process of the signal frame includes: receiving a baseband signal, taking N sampling point signals each time, and then sliding 1 sampling point in turn, then taking N sampling point signals, and calculating whether the energy exceeds the maximum value of signal acquisition
  • the threshold of one-tenth, the local preamble is used to calculate whether the correlation peak exceeds the threshold of half of the maximum value and perform feature matching, and finally the signal frame is successfully received, where N is a positive integer;
  • the method for separately calculating the complex cross-correlation function between the two segments of the signal in the long amble group and the short amble group includes: separately calculating the sampling points of the short amble group and the sampling points of the long amble group After performing a cyclic shift operation of shifting 1 bit to the right each time, performing complex multiplication according to the sampling point, and then accumulating, the complex cross-correlation function is obtained.
  • the embodiment of the present invention also provides a radio frequency fingerprint extraction device, including:
  • the receiving module is used to allow the wireless receiver to take out all the preamble signals from the received signal frame;
  • the removal module is used to remove the carrier frequency offset in the preamble through signal interpolation to achieve carrier synchronization
  • the grouping module is used to divide the preamble signal into a long preamble group and a short preamble group, and each group is divided into two segment signals before and after, specifically: using the local preamble signal and the interpolated received preamble signal to calculate A cross-correlation function to accurately determine the time point of the boundary between the long amble group and the short amble group, and then divide the two segment signals in each group;
  • the first calculation module is configured to calculate the complex cross-correlation function between the two segments of signals in the long amble group and the short amble group respectively;
  • the second calculation module is configured to calculate the power spectrum of the long amble group and the short amble group signals respectively;
  • the third calculation module is used to calculate the power spectrum difference between the long amble group and the short amble group signal to obtain a radio frequency fingerprint.
  • the power spectrum difference between the long amble group and the short amble group signal is specifically for:
  • GDD(k) is the complex cross-correlation between the two segments of the signal in the short code group
  • GCC(k) is the Fourier transform of the complex cross-correlation function between the two signals in the long code group
  • the complex cross-correlation function between the long amble group and the two segments of signals in the short amble group calculated by the first calculation module is specifically:
  • the second calculation module is also used to perform Fourier transform on the complex cross-correlation function between the two segments of the signal in the short amble group and the long amble group to obtain
  • An embodiment of the present invention also provides a wireless receiver, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and the processor implements the radio frequency fingerprint extraction method when the program is executed.
  • the embodiment of the present invention also provides a computer-readable storage medium that stores computer-executable instructions, and the computer-executable instructions are used to execute the radio frequency fingerprint extraction method.
  • the radio frequency fingerprint extraction method of the embodiment of the present invention uses a series of operations between several symbols in the preamble signal of the received frame, including cross-correlation operations, Fourier transform, power spectrum division, etc., to remove the influence of channel additive noise and channel A method for extracting radio frequency fingerprints under the influence of multipath effects; compared with existing methods, the transmitter radio frequency fingerprints extracted by the embodiment of the present invention are less affected by the wireless channel and are more pure, and can be used for radio frequency fingerprint technology.
  • High-precision identification transmitters provide technical means; the embodiments of the present invention are applicable to various communication systems with a preamble frame structure composed of multiple different symbols, especially broadband communication systems.
  • FIG. 1 is a flowchart of a method for extracting a radio frequency fingerprint based on a preamble signal power spectrum difference according to an embodiment of the present invention
  • Figure 2 is a schematic diagram of the acquisition and synchronization process of the signal frame by the receiver
  • Fig. 3 is a schematic diagram of grouping and segmentation of leading symbols in the embodiment of Fig. 1;
  • FIG. 4 is a schematic diagram of the cross-correlation operation of two segments of signals in the long amble group and the short amble group in the embodiment of FIG.
  • FIG. 5 is a schematic diagram of the power spectrum difference operation between the long code group and the short code group in the embodiment of FIG. 1;
  • Fig. 6 is a schematic diagram of the polar coordinate form of the radio frequency fingerprint
  • Figure 7 is an IEEE802.11gOFDM frame structure diagram in an embodiment of the present invention.
  • Fig. 8 is a schematic diagram of a preamble grouping and segmentation method of an IEEE802.11g signal frame
  • Fig. 9 is a schematic diagram of the radio frequency fingerprint of the extracted IEEE802.11g signal frame.
  • This embodiment is about a radio frequency fingerprint extraction method, including the acquisition and synchronization of the received signal, removing the carrier frequency offset, and performing cross-correlation calculations and Fourier changes on two sets of different preamble signals, and then dividing by Calculate the RF fingerprint result. As shown in Figure 1, it includes the following steps:
  • the wireless receiver takes out all the preamble signals from the received signal frame.
  • the receiving process of the signal frame includes: receiving the baseband signal, each time taking N sampling point signals, and then sliding 1 in turn After sampling points, take N sampling point signals, calculate whether the energy exceeds the threshold of one-tenth of the maximum value of the signal acquisition, use the local preamble to calculate whether the correlation peak exceeds the threshold of half the maximum value and perform feature matching, and finally receive the signal successfully Frame, where N is a positive integer;
  • Step2 Remove the carrier frequency offset in the preamble by signal interpolation to achieve carrier synchronization
  • Step3 Divide the preamble signal into a long preamble group and a short preamble group, and divide each group into two signals before and after.
  • the preamble structure after division is shown in Figure 3, where d1 and d2 are short preambles. , C1, c2 are the long preamble;
  • Step4 Calculate the complex cross-correlation function between the two segments of the long amble group and the short amble group respectively, as shown in Figure 4, where the long amble group and the short amble group are calculated separately
  • the method of the complex cross-correlation function between the two segments of the signal in the group includes: respectively performing a cyclic shift operation of shifting the sampling points of the short code group and the sampling point of the long code group to the right by 1 bit each time and pressing The sampling points are multiplied by complex numbers and then accumulated to obtain the complex cross-correlation function;
  • the complex cross-correlation functions between the two segments of signals in the long code group and the short code group are:
  • the content of the transmitted signal corresponding to d1, d2 and c1, c2 must be different.
  • Step5 Calculate the power spectrum of the signal of the long code group and the short code group respectively;
  • Step6 Calculate the power spectrum difference between the long amble group and the short amble group signal, and obtain the radio frequency fingerprint by dividing the long amble group and the short amble group signals, and the result is shown in Figure 5 .
  • the difference of the power spectrum of the signal of the long pilot code group and the short pilot code group is,
  • the radio frequency fingerprint is presented graphically on a two-dimensional plane, as shown in Figure 6.
  • the frame structure of the OFDM preamble in the IEEE802.11g communication system is shown in Figure 7.
  • the preamble is divided into two groups: short preamble and long preamble, each occupying 8us.
  • the short amble group is composed of 10 short ambles t1, t2,..., t10, and each short amble is composed of 12 subcarriers;
  • the long amble group is composed of 2 long ambles T1, T2 and a cyclic prefix G12 composition.
  • the short code group (2 ⁇ 3.2us) and the long code group (2 ⁇ 3.2us) are respectively divided into two segments of equal length, and each segment occupies 3.2us. As shown in Figure 8.
  • the frame structure shown in FIG. 8 is captured from the received signal using the frame capturing method shown in FIG. 2, and coarse synchronization is performed. Then, the signal interpolation method is used to increase the sampling rate, and then the local preamble signal and the interpolated received preamble signal are used to calculate the cross-correlation function to accurately determine the boundary time between the short preamble group and the long preamble group shown in Figure 8. Point (that is, the dividing point between t10 and G12), and then divide the signal segments of d1, d2, c1, and c2.
  • the short amble signals at t1 and t2 are distorted; the G12 signal before the long amble also has instability problems. Therefore, t3 ⁇ t10 are selected as the short code group, and T1 and T2 are used as the long code group, each occupying 2 ⁇ 3.2us.
  • the received signals of d1, d2, c1, and c2 shown in Figure 8 are y d1 (n), y d2 (n), y c1 (n), and y c2 (n), respectively.
  • the signals are all complex signals. Calculate the cross-correlation functions of y d1 (n) and y d2 (n) respectively, namely
  • Represents the conjugate operation, l 0,1,...,N-1.
  • the bandwidth of the OFDM complex signal is 20MHz, and the sampling rate is 20MHz.
  • the time lengths of the short codes d1 and d2 are both 3.2us, the corresponding number of sampling points is 32, and there are 64 sampling points after 2 times interpolation.
  • the time lengths of the long leading codes c1 and c2 are also 3.2us, the corresponding number of sampling points is 32 points, and there are 64 sampling points after 2 times interpolation. therefore, with The cross-correlation length of is 64 points, and the cyclic cross-correlation operation shown in Figure 4 is used.
  • FFT Fast Fourier Transform
  • each short amble t3 to t10 is composed of 12 subcarriers, and the long amble is composed of 52 subcarriers.
  • the FFT results of these 12 frequency points are meaningful.
  • the FFT results of other frequency points are meaningful.
  • the value of the RF fingerprint in step 4 is a complex number, which is expressed in polar coordinates as
  • means taking the amplitude operation
  • ⁇ (k) is taking the phase of R FF (k)
  • k ⁇ 6,10,14,18,22,26,37,41,45,49, 53, 57 ⁇ .
  • FIG. 9 A typical radio frequency fingerprint map formed by this embodiment is shown in FIG. 9.
  • the embodiment of the present invention also provides a radio frequency fingerprint extraction device, including:
  • the receiving module is used to allow the wireless receiver to take out all the preamble signals from the received signal frame;
  • the removal module is used to remove the carrier frequency offset in the preamble through signal interpolation to achieve carrier synchronization
  • the grouping module is used to divide the preamble signal into a long preamble group and a short preamble group, and each group is divided into two segment signals before and after, specifically: using the local preamble signal and the interpolated received preamble signal to calculate A cross-correlation function to accurately determine the time point of the boundary between the long amble group and the short amble group, and then divide the two segment signals in each group;
  • the first calculation module is configured to calculate the complex cross-correlation function between the two segments of signals in the long amble group and the short amble group respectively;
  • the second calculation module is configured to calculate the power spectrum of the long amble group and the short amble group signals respectively;
  • the third calculation module is used to calculate the power spectrum difference between the long amble group and the short amble group signal to obtain a radio frequency fingerprint.
  • the complex cross-correlation function between the long amble group and the two segments of signals in the short amble group calculated by the first calculation module is specifically:
  • the second calculation module is also used to perform Fourier transform on the complex cross-correlation function between the two segments of the signal in the short amble group and the long amble group to obtain
  • a wireless receiver includes a memory, a processor, and a computer program that is stored on the memory and can run on the processor, and the processor implements the radio frequency fingerprint extraction method when the program is executed.
  • the embodiment of the present invention adds a self-learning function to the wireless receiver, performs corresponding identification, storage, and processing of abnormal terminals, and creates a good network environment for users by restricting the behavior of the terminals. It overcomes the problems and defects of abnormal terminals in the prior art that continue to request network access, waste air interface resources of the wireless receiver, and aggravate network congestion.
  • the embodiment of the present invention also provides a computer-readable storage medium that stores computer-executable instructions, and the computer-executable instructions are used to execute the radio frequency fingerprint extraction method.
  • the above-mentioned storage medium may include, but is not limited to: U disk, read only memory (ROM, ReadOnlyMemory), random access memory (RAM, RandomAccessMemory), mobile hard disk, magnetic disk or optical disk, etc., which can store various programs.
  • U disk read only memory
  • RAM ReadOnlyMemory
  • RAM RandomAccessMemory
  • mobile hard disk magnetic disk or optical disk, etc.
  • magnetic disk or optical disk etc.
  • Such software may be distributed on a computer-readable medium, and the computer-readable medium may include a computer storage medium (or a non-transitory medium) and a communication medium (or a transitory medium).
  • the term computer storage medium includes volatile and non-volatile data implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Sexual, removable and non-removable media.
  • Computer storage media include but are not limited to RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or Any other medium used to store desired information and that can be accessed by a computer.
  • communication media usually contain computer-readable instructions, data structures, program modules, or modulated data signals such as carrier waves or other transmission mechanisms.

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Abstract

本发明实施例公开了一种射频指纹提取方法、装置、无线接收机及存储介质，其中，所述射频指纹提取方法，包括：无线接收机从接收到的信号帧中取出全部前导符信号；通过信号内插去除前导符中的载波频偏，实现载波同步；将前导符信号分为长导码组和短导码组，将每组分为前后两个段信号；分别计算长导码组和短导码组内两段信号之间的复互相关函数；分别计算长导码组和短导码组信号的功率谱；计算长导码组和短导码组信号的功率谱差异，得到射频指纹。在本发明实施例中，射频指纹提取方法受无线信道的影响小，更为纯净，进而可为利用射频指纹技术高精度识别发射机提供技术手段。

Description

射频指纹提取方法、装置、无线接收机及存储介质 技术领域
本发明涉及通信与信息安全技术领域，尤指一种射频指纹提取方法、装置、无线接收机及存储介质。
背景技术
射频指纹(RFF)是无线发射设备的固有特征，它是发射信号经过发射机电路引起的微小的信号畸变。发射机中包含放大器、滤波器、变频器、加法器、振荡器、功放、天线等许多器件，由于制造工艺的偏差，这些器件的特性不可能完全一致，以至于任何一台发射设备都不可能具有完全相同的射频指纹。
RFF是器件引起的特性，因而具有长时稳定性和唯一性。RFF的这种特性可用来识别无线发射机，也可以用来对发射机的身份进行认证从而保护通信安全，也可用于无线网络对终端实施接入管控。RFF是由发射机产生、寄生在接收信号上的一种微弱信号。它的产生机理很复杂，可以用实验观察到射频指纹的存在，但却难以用数学来表达，因而难以找到理论上提取射频指纹的方法。特别是无线信道的多径效应与发射信号是卷积关系，而射频指纹在一定程度上也与发送信号呈卷积关系，要去除多径效应必然伤及射频指纹，因而多径效应很大程度上限制了射频指纹的精确提取。另外，信道噪声也是射频指纹的干扰项，去除加性噪声需要利用相关运算等累加操作，而累加操作又会模糊射频指纹的细节。因此，从一帧信号的前导符中直接去除信道噪声就非常困难。
因此，受到环境噪声和无线传输信道多径效应的影响，接收信号可能会产生严重的畸变，从接收信号中提取微弱的射频指纹信号非常的困难，特别是对于宽带信号而言更是如此。从目前公开的文献看，尚未出现能够从理论上寻找到真正抵抗随机噪声和多径效应的射频指纹提取方法。
发明内容
本发明实施例提供了一种射频指纹提取方法、装置、无线接收机及存储介质，从无线通信的信号帧结构中寻找突破点，利用信号帧前导符中通常存在多个不同符号的特点，这些符号通常用来捕获信号帧、校正载波频偏、自动增益控制、信道估计以及实现符号的精确同步等，在本发明实施例中，这些前导符除了仍然具有上述作用以外，还被利用来提取射频指纹。
本发明实施例提供了一种射频指纹提取方法，包括：
无线接收机从接收到的信号帧中取出全部前导符信号；通过信号内插去除前导符中的载波频偏，实现载波同步；将前导符信号分为长导码组和短导码组，将每组分为前后两个段信号，具体为：用本地前导符信号与内插后的接收前导符信号计算互相关函数，精确确定所述长导码组和所述短导码组的分界时间点，进而划分出每组内的两个段信号；分别计算所述长导码组和所述短导码组内两段信号之间的复互相关函数；分别计算所述长导码组和所述短导码组信号的功率谱；计算所述长导码组和所述短导码组信号的功率谱差异，得到射频指纹，所述长导码组和所述短导码组信号的功率谱差异具体为：R FF(k)＝GDD(k)/GCC(k)＝P dd(k)/P cc(k)，其中GDD(k)为所述短导码组内两段信号之间的复互相关函数的傅里叶变换，GCC(k)为所述长导码组内两段信号之间的复互相关函数的傅里叶变换，P dd(k)和P cc(k)分别为所述短导码组和所述长导码组信号的功率谱，k＝0，1，...，N-1。
进一步的，所述分别计算所述长导码组和所述短导码组内两段信号之间的复互相关函数具体为：
Figure PCTCN2020110426-appb-000001
Figure PCTCN2020110426-appb-000002
其中
Figure PCTCN2020110426-appb-000003
表示求共轭操作，E[·]表示求期望运算，l＝0，1，...，N-1，
接收信号
y d1(n)＝s d1(n)*h(n)+v(n)
y d2(n)＝s d2(n)*h(n)+v(n)
y c1(n)＝s c1(n)*h(n)+v(n)
y c2(n)＝s c2(n)*h(n)+v(n)
其中d1和d2为短导码组内的两段符号，s d1(n)和s d2(n)为对应的发送信号；c1和c2为长导码组内的两段符号，s c1(n)和s c2(n)为对应的发送信号，n＝0，1，...，N-1，为采样点的序数；h(n)为多径信道，“*”表示线性卷积运算，v(n)为加性噪声。
进一步的，所述短导码组符号d1和d2与所述长导码组符号c1和c2对应的发送信号内容不同。
进一步的，所述计算所述长导码组和所述短导码组信号的功率谱具体为：对所述短导码组和所述长导码组内两段信号之间的复互相关函数做傅里叶变换，得到
GDD(k)＝FFT[G d1d2(l)]＝P dd(k)|H(k)| 2
和GCC(k)＝FFT[G c1c2(l)]＝P cc(k)|H(k)| 2
当s d1(n)＝s d2(n)、s c1(n)＝s c2(n)时，有
P dd(k)＝|FFT[s d1(n)]| 2＝|FFT[s d2(n)]| 2
P cc(k)＝|FFT[s c1(n)]| 2＝|FFT[s c2(n)]| 2，
H(k)＝FFT[h(n)]，k＝0，1，...，N-1。
进一步的，所述射频指纹提取方法还包括将所述射频指纹以图形方式呈现在二维平面上。
进一步的，所述信号帧的接收过程，包括：接收基带信号，每次取N个采样点信号，再依次滑动1个采样点后取N个采样点信号，计算能量是否超过信号采集最大值的十分之一的门限，利用本地前导符计算相关峰值是否超过最大值一半的门限并进行特征匹配，最终成功接收信号帧，其中，N为正整数；
所述分别计算所述长导码组和所述短导码组内两段信号之间的复互相关函数的方法，包括：分别将短导码组的采样点和长导码组的采样点进行每次循环右移1位的循环移位操作后并按采样点进行复数相乘，然后累加，得到所述复互相关函数。
本发明实施例还提供一种射频指纹提取的装置，包括：
接收模块，用于让无线接收机从接收到的信号帧中取出全部前导符信号；
去除模块，用于通过信号内插去除前导符中的载波频偏，实现载波同步；
分组模块，用于将前导符信号分为长导码组和短导码组，将每组分为前后两个段信号，具体为：用本地前导符信号与内插后的接收前导符信号计算互相关函数，精确确定所述长导码组和所述短导码组的分界时间点，进而划分出每组内的两个段信号；
第一计算模块，用于分别计算所述长导码组和所述短导码组内两段信号之间的复互相关函数；
第二计算模块，用于分别计算所述长导码组和所述短导码组信号的功率谱；
第三计算模块，用于计算所述长导码组和所述短导码组信号的功率谱差异，得到射频指纹，所述长导码组和所述短导码组信号的功率谱差异具体为：
R FF(k)＝GDD(k)/GCC(k)＝P dd(k)/P cc(k)，其中GDD(k)为所述短导码组内两段信号之间的复互相关函数的傅里叶变换，GCC(k)为所述长导码组内两段信号之间的复互相关函数的傅里叶变换，P dd(k)和P cc(k)分别为所述短导码组和所述长导码组信号的功率谱，k＝0，1，...，N-1。
进一步的，所述第一计算模块计算而得的所述长导码组和所述短导码组内两段信号之间的复互相关函数具体为：
Figure PCTCN2020110426-appb-000004
Figure PCTCN2020110426-appb-000005
其中
Figure PCTCN2020110426-appb-000006
表示求共轭操作，E[·]表示求期望运算，l＝0，1，...，N-1，
接收信号
y d1(n)＝s d1(n)*h(n)+v(n)
y d2(n)＝s d2(n)*h(n)+v(n)
y c1(n)＝s c1(n)*h(n)+v(n)
y c2(n)＝s c2(n)*h(n)+v(n)
其中d1和d2为短导码组内的两段符号，s d1(n)和s d2(n)为对应的发送信号；c1和c2为长导码组内的两段符号，s c1(n)和s c2(n)为对应的发送信号，n＝0，1，...，N-1，为采样点的序数；h(n)为多径信道，“*”表示线性卷积运算，v(n)为加性噪声；
所述第二计算模块还用于对所述短导码组和所述长导码组内两段信号之间的复互相关函数做傅里叶变换，得到
GDD(k)＝FFT[G d1d2(l)]＝P dd(k)|H(k)| 2
和GCC(k)＝FFT[G c1c2(l)]＝P cc(k)|H(k)| 2
当s d1(n)＝s d2(n)、s c1(n)＝s c2(n)时，有
P dd(k)＝|FFT[s d1(n)]| 2＝|FFT[s d2(n)]| 2
P cc(k)＝|FFT[s c1(n)]| 2＝|FFT[s c2(n)]| 2，
H(k)＝FFT[h(n)]，k＝0，1，...，N-1。
本发明实施例还提供一种无线接收机，包括存储器、处理器及存储在存储器上并可在 处理器上运行的计算机程序，所述处理器执行所述程序时实现所述射频指纹提取方法。
本发明实施例还提供一种计算机可读存储介质，存储有计算机可执行指令，所述计算机可执行指令用于执行所述射频指纹提取方法。
本发明实施例的射频指纹提取方法利用接收帧前导信号中的若干个符号之间进行一系列运算，包括互相关运算、傅里叶变换、功率谱相除等，去除信道加性噪声影响和信道多径效应影响，进而提取出射频指纹的方法；与已有方法相比，本发明实施例所提取的发射机射频指纹，受无线信道的影响小，更为纯净，进而可为利用射频指纹技术高精度识别发射机提供技术手段；本发明实施例适用于由多个不同符号组成的前导符帧结构的各种通信体制，特别是宽带通信体制。
本发明的其它特征和优点将在随后的说明书中阐述，并且，部分地从说明书中变得显而易见，或者通过实施本发明而了解。本发明的目的和其他优点可通过在说明书、权利要求书以及附图中所特别指出的结构来实现和获得。
附图说明
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为本发明实施例基于前导符信号功率谱差异的射频指纹提取方法的流程图；
图2为接收机对信号帧的捕获和同步过程示意图；
图3为图1实施例中前导符号的分组和分段示意图；
图4为图1实施例中长导码组和短导码组内两段信号的互相关运算示意图；
图5为图1实施例中长导码组和短导码组之间功率谱差异运算示意图；
图6为射频指纹的极坐标形式示意图；
图7为本发明一实施方式中IEEE802.11gOFDM帧结构图；
图8为IEEE802.11g信号帧的前导符分组和分段方法示意图；
图9为提取的IEEE802.11g信号帧的射频指纹示意图。
具体实施方式
下文中将结合附图对本发明的实施例进行详细说明。应当理解，此处所描述的具体实施例仅仅用以解释本发明，并不用于限定本发明。
在附图的流程图示出的步骤可以在诸如一组计算机可执行指令的计算机系统中执行。 并且，虽然在流程图中示出了逻辑顺序，但是在某些情况下，可以以不同于此处的顺序执行所示出或描述的步骤。
本实施例是关于一种射频指纹提取方法，包括了接收信号的捕获与同步，去除载波频偏，将两组不同的前导符信号分别做互相关计算和傅里叶变化后，再通过相除计算射频指纹结果。如图1所示，包括以下步骤：
Step1、无线接收机从接收到的信号帧中取出全部前导符信号，其中信号帧的接收过程，如图2所示，包括：接收基带信号，每次取N个采样点信号，再依次滑动1个采样点后取N个采样点信号，计算能量是否超过信号采集最大值的十分之一的门限，利用本地前导符计算相关峰值是否超过最大值一半的门限并进行特征匹配，最终成功接收信号帧，其中，N为正整数；
Step2、通过信号内插去除前导符中的载波频偏，实现载波同步；
Step3、将前导符信号分为长导码组和短导码组，将每组分为前后两个段信号，经过划分后的前导符结构如图3所示，其中d1，d2为短导码，c1，c2为长导码；
Step4、分别计算所述长导码组和所述短导码组内两段信号之间的复互相关函数，如图4所示，其中分别计算所述长导码组和所述短导码组内两段信号之间的复互相关函数的方法，包括：分别将短导码组的采样点和长导码组的采样点进行每次循环右移1位的循环移位操作后并按采样点进行复数相乘，然后累加，得到所述复互相关函数；
其中长导码组和短导码组内两段信号之间的复互相关函数分别为：
Figure PCTCN2020110426-appb-000007
Figure PCTCN2020110426-appb-000008
其中
Figure PCTCN2020110426-appb-000009
表示求共轭操作，E[·]表示求期望运算，l＝0，1，...，N-1，接收信号
y d1(n)＝s d1(n)*h(n)+v 1(n)
y d2(n)＝s d2(n)*h(n)+v 2(n)
y c1(n)＝s c1(n)*h(n)+v 3(n)
y c2(n)＝s c2(n)*h(n)+v 4(n)
其中d1和d2为短导码组内的两段符号，s d1(n)和s d2(n)为对应的发送信号；c1和c2为长导码组内的两段符号，s c1(n)和s c2(n)为短导码组内的两段符号，n＝0，1，...，N-1，为采样点的序数；h(n)为多径信道，“*”表示线性卷积运算，v(n)为加性噪声。d1、d2和c1、 c2对应的发送信号内容必须不相同。
Step5、分别计算所述长导码组和所述短导码组信号的功率谱；
对所述长导码组和所述短导码组内两段信号之间的复互相关函数做傅里叶变换，得到
Figure PCTCN2020110426-appb-000010
和
Figure PCTCN2020110426-appb-000011
当s d1(n)＝s d2(n)、s c1(n)＝s c2(n)时，有
P dd(k)＝|FFT[s d1(n)]| 2＝|FFT[s d2(n)]| 2
P cc(k)＝|FFT[s c1(n)]| 2＝|FFT[s c2(n)]| 2，
P dd(k)和P cc(k)分别为每段对应的发送信号的功率谱，H(k)＝FFT[h(n)]，k＝0，1，...，N-1。
Step6、计算所述长导码组和所述短导码组信号的功率谱差异，通过将长导码组和短导码组的信号进行相除，得到射频指纹，其结果如图5所示。
长导码组和短导码组信号的功率谱差异为，
R FF(k)＝GDD(k)/GCC(k)＝P dd(k)/P cc(k)。射频指纹以图形方式呈现在二维平面上，如图6所示。
下面以IEEE802.11g通信体制为例对本实施例的方法进一步描述。
1、将前导符分组和分段
IEEE802.11g通信体制中的OFDM型前导符的帧结构如图7所示。在该帧结构中，前导符分为短导码和长导码两个组，各占8us。其中短导码组由10个短导码t1、t2、...、t10组成，每个短导码由12个子载波组成；长导码组由2个长导码T1、T2和一个循环前缀G12组成。
根据本发明的技术要求，分别将短导码组(2×3.2us)和长导码组(2×3.2us)分为等长的两个段，每段占时3.2us。如图8所示。
在接收机中，采用图2所示的帧捕获方法从接收信号中捕获到图8的所示的帧结构，并进行粗同步。然后，通过信号内插方法提高采样率，再用本地前导符信号与内插后的接 收前导符信号计算互相关函数，精确确定图8所示的短导码组与长导码组的分界时刻点(即t10与G12之间的分界点)，进而划分出d1、d2、c1、c2的信号片段。
由于发射机响应和信道响应的存在，t1和t2短导码信号失真较大；同样长导码前面的G12信号也存在不稳定问题。因此，选择t3～t10作为短导码组，T1和T2作为长导码组，各占2×3.2us。
2、计算各段信号之间的互相关函数
假设在接收机中，图8所示的d1、d2、c1、c2的各段接收信号分别为y d1(n)、y d2(n)、y c1(n)和y c2(n)，这些信号都是复数信号。分别计算y d1(n)、y d2(n)互相关函数，即
Figure PCTCN2020110426-appb-000012
以及y c1(n)和y c2(n)的互相关函数，即
Figure PCTCN2020110426-appb-000013
其中
Figure PCTCN2020110426-appb-000014
表示取共轭操作，l＝0，1，...，N-1。对于802.11g信号，OFDM复数信号的带宽为20MHz，采样率为20MHz。短导码d1、d2的时间长度都为3.2us，对应的采样点数为32点，采用2倍内插后有64个采样点。长导码c1、c2的时间长度也都为3.2us，对应的采样点数为32点，采用2倍内插后有64个采样点。因此，
Figure PCTCN2020110426-appb-000015
和
Figure PCTCN2020110426-appb-000016
的互相关长度为64点，且采用图4所示的循环互相关运算。
3、计算每组信号的功率谱
采用64点的快速傅里叶变换(FFT)运算，将步骤2中的两个公式变换到频域，即
Figure PCTCN2020110426-appb-000017
Figure PCTCN2020110426-appb-000018
k＝0，1，2，...，63。根据802.11g标准，每个短导码t3～t10都是由12个子载波构成，长导码由52个子载波构成。因此，在
Figure PCTCN2020110426-appb-000019
的64个值中，只有k＝{6，10，14，18，22，26，37，41，45，49，53，57}这12个频点的FFT结果有意义。
Figure PCTCN2020110426-appb-000020
中除了k＝{0，1，2，3，4，5，32，58，59，60，61，62，63}点外的其它频点的FFT结果有意义。
4、将两组信号的功率谱相除
将
Figure PCTCN2020110426-appb-000021
除以
Figure PCTCN2020110426-appb-000022
即
R FF(k)＝GDD(k)/GCC(k)
从上式中，取出k＝{6，10，14，18，22，26，37，41，45，49，53，57}对应的R FF(k)值作为射频指纹。
5、以极坐标的方式展现射频指纹
步骤4中射频指纹的值是复数，将其表示成极坐标的形式为
R FF(k)＝|R FF(k)|e jθ(k)
其中“|·|”表示取幅度运算，“θ(k)”是取R FF(k)的相位，k＝{6，10，14，18，22，26，37，41，45，49，53，57}。
将极坐标形式的结果绘制在二维平面上，即形成射频指纹。这种方式可以将指纹细节进行展现，便于观察和比对。采用本实施例形成的典型的射频指纹图如图9所示。
本发明实施例还提供一种射频指纹提取的装置，包括：
接收模块，用于让无线接收机从接收到的信号帧中取出全部前导符信号；
去除模块，用于通过信号内插去除前导符中的载波频偏，实现载波同步；
分组模块，用于将前导符信号分为长导码组和短导码组，将每组分为前后两个段信号，具体为：用本地前导符信号与内插后的接收前导符信号计算互相关函数，精确确定所述长导码组和所述短导码组的分界时间点，进而划分出每组内的两个段信号；
第一计算模块，用于分别计算所述长导码组和所述短导码组内两段信号之间的复互相关函数；
第二计算模块，用于分别计算所述长导码组和所述短导码组信号的功率谱；
第三计算模块，用于计算所述长导码组和所述短导码组信号的功率谱差异，得到射频指纹，所述长导码组和所述短导码组信号的功率谱差异具体为：R FF(k)＝GDD(k)/GCC(k)＝P dd(k)/P cc(k)，其中GDD(k)为所述短导码组内两段信号之间的复互相关函数的傅里叶变换，GCC(k)为所述长导码组内两段信号之间的复互相关函数的傅里叶变换，P dd(k)和P cc(k)分别为所述短导码组和所述长导码组信号的功率谱，k＝0，1，...，N-1。
所述第一计算模块计算而得的所述长导码组和所述短导码组内两段信号之间的复互相关函数具体为：
Figure PCTCN2020110426-appb-000023
Figure PCTCN2020110426-appb-000024
其中
Figure PCTCN2020110426-appb-000025
表示求共轭操作，E[·]表示求期望运算，l＝0，1，...，N-1，
接收信号
y d1(n)＝s d1(n)*h(n)+v(n)
y d2(n)＝s d2(n)*h(n)+v(n)
y c1(n)＝s c1(n)*h(n)+v(n)
y c2(n)＝s c2(n)*h(n)+v(n)
其中d1和d2为短导码组内的两段符号，s d1(n)和s d2(n)为对应的发送信号；c1和c2为长导码组内的两段符号，s c1(n)和s c2(n)为对应的发送信号，n＝0，1，...，N-1，为采样点的序数；h(n)为多径信道，“*”表示线性卷积运算，v(n)为加性噪声；
所述第二计算模块还用于对所述短导码组和所述长导码组内两段信号之间的复互相关函数做傅里叶变换，得到
GDD(k)＝FFT[G d1d2(l)]＝P dd(k)|H(k)| 2
和GCC(k)＝FFT[G c1c2(l)]＝P cc(k)|H(k)| 2
当s d1(n)＝s d2(n)、s c1(n)＝s c2(n)时，有
P dd(k)＝|FFT[s d1(n)]| 2＝|FFT[s d2(n)]| 2
P cc(k)＝|FFT[s c1(n)]| 2＝|FFT[s c2(n)]| 2，
H(k)＝FFT[h(n)]，k＝0，1，...，N-1。
一种无线接收机，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述程序时实现所述射频指纹提取方法。
其中，本发明的实施例为无线接收机增加了自学习功能，对异常终端进行相应的识别、存储和处理，通过限制终端的行为，为用户营造良好的网络环境。克服了现有技术中存在的异常终端持续请求入网，浪费无线接收机的空口资源，加重网络拥塞的问题和缺陷。
本发明实施例还提供一种计算机可读存储介质，存储有计算机可执行指令，所述计算机可执行指令用于执行所述射频指纹提取方法。
在本实施例中，上述存储介质可以包括但不限于：U盘、只读存储器(ROM， ReadOnlyMemory)、随机存取存储器(RAM，RandomAccessMemory)、移动硬盘、磁碟或者光盘等各种可以存储程序代码的介质。
本领域普通技术人员可以理解，上文中所公开方法中的全部或某些步骤、系统、装置中的功能模块/单元可以被实施为软件、固件、硬件及其适当的组合。在硬件实施方式中，在以上描述中提及的功能模块/单元之间的划分不一定对应于物理组件的划分；例如，一个物理组件可以具有多个功能，或者一个功能或步骤可以由若干物理组件合作执行。某些组件或所有组件可以被实施为由处理器，如数字信号处理器或微处理器执行的软件，或者被实施为硬件，或者被实施为集成电路，如专用集成电路。这样的软件可以分布在计算机可读介质上，计算机可读介质可以包括计算机存储介质(或非暂时性介质)和通信介质(或暂时性介质)。如本领域普通技术人员公知的，术语计算机存储介质包括在用于存储信息(诸如计算机可读指令、数据结构、程序模块或其他数据)的任何方法或技术中实施的易失性和非易失性、可移除和不可移除介质。计算机存储介质包括但不限于RAM、ROM、EEPROM、闪存或其他存储器技术、CD-ROM、数字多功能盘(DVD)或其他光盘存储、磁盒、磁带、磁盘存储或其他磁存储装置、或者可以用于存储期望的信息并且可以被计算机访问的任何其他的介质。此外，本领域普通技术人员公知的是，通信介质通常包含计算机可读指令、数据结构、程序模块或者诸如载波或其他传输机制之类的调制数据信号。

Claims (10)

  1. 一种射频指纹提取方法，其特征在于，包括：
    无线接收机从接收到的信号帧中取出全部前导符信号；
    通过信号内插去除前导符中的载波频偏，实现载波同步；
    将前导符信号分为长导码组和短导码组，将每组分为前后两个段信号，具体为：用本地前导符信号与内插后的接收前导符信号计算互相关函数，精确确定所述长导码组和所述短导码组的分界时间点，进而划分出每组内的两个段信号；
    分别计算所述长导码组和所述短导码组内两段信号之间的复互相关函数；
    分别计算所述长导码组和所述短导码组信号的功率谱；
    计算所述长导码组和所述短导码组信号的功率谱差异，得到射频指纹，所述长导码组和所述短导码组信号的功率谱差异具体为：R FF(k)＝GDD(k)/GCC(k)＝P dd(k)/P cc(k)，其中GDD(k)为所述短导码组内两段信号之间的复互相关函数的傅里叶变换，GCC(k)为所述长导码组内两段信号之间的复互相关函数的傅里叶变换，P dd(k)和P cc(k)分别为所述短导码组和所述长导码组信号的功率谱，k＝0，1，...，N-1。
  2. 根据权利要求1所述的射频指纹提取方法，其特征在于，所述分别计算所述长导码组和所述短导码组内两段信号之间的复互相关函数具体为：
    Figure PCTCN2020110426-appb-100001
    Figure PCTCN2020110426-appb-100002
    其中
    Figure PCTCN2020110426-appb-100003
    表示求共轭操作，E[·]表示求期望运算，l＝0，1，...，N-1，
    接收信号
    y d1(n)＝s d1(n)*h(n)+v(n)
    y d2(n)＝s d2(n)*h(n)+v(n)
    y c1(n)＝s c1(n)*h(n)+v(n)
    y c2(n)＝s c2(n)*h(n)+v(n)
    其中d1和d2为短导码组内的两段符号，s d1(n)和s d2(n)为对应的发送信号；c1和c2为长导码组内的两段符号，s c1(n)和s c2(n)为对应的发送信号，n＝0，1，...，N-1，为采样点的序数；h(n)为多径信道，“*”表示线性卷积运算，v(n)为加性噪声。
  3. 根据权利要求2所述的射频指纹提取方法，其特征在于，所述短导码组符号d1 和d2与所述长导码组符号c1和c2对应的发送信号内容不同。
  4. 根据权利要求2所述的射频指纹提取方法，其特征在于，所述计算所述长导码组和所述短导码组信号的功率谱具体为：对所述短导码组和所述长导码组内两段信号之间的复互相关函数做傅里叶变换，得到
    GDD(k)＝FFT[G d1d2(l)]＝P dd(k)|H(k)| 2
    和GCC(k)＝FFT[G c1c2(l)]＝P cc(k)|H(k)| 2
    当s d1(n)＝s d2(n)、s c1(n)＝s c2(n)时，有
    P dd(k)＝|FFT[s d1(n)]| 2＝|FFT[s d2(n)]| 2
    P cc(k)＝|FFT[s c1(n)]| 2＝|FFT[s c2(n)]| 2，
    H(k)＝FFT[h(n)]，k＝0，1，...，N-1。
  5. 根据权利要求1所述的射频指纹提取方法，其特征在于，该方法还包括将所述射频指纹以图形方式呈现在二维平面上。
  6. 根据权利要求1所述的射频指纹提取方法，其特征在于，所述信号帧的接收过程，包括：接收基带信号，每次取N个采样点信号，再依次滑动1个采样点后取N个采样点信号，计算能量是否超过信号采集最大值的十分之一的门限，利用本地前导符计算相关峰值是否超过最大值一半的门限并进行特征匹配，最终成功接收信号帧，其中，N为正整数；
    所述分别计算所述长导码组和所述短导码组内两段信号之间的复互相关函数的方法，包括：分别将短导码组的采样点和长导码组的采样点进行每次循环右移1位的循环移位操作后并按采样点进行复数相乘，然后累加，得到所述复互相关函数。
  7. 一种射频指纹提取的装置，其特征在于，包括：
    接收模块，用于让无线接收机从接收到的信号帧中取出全部前导符信号；
    去除模块，用于通过信号内插去除前导符中的载波频偏，实现载波同步；
    分组模块，用于将前导符信号分为长导码组和短导码组，将每组分为前后两个段信号，具体为：用本地前导符信号与内插后的接收前导符信号计算互相关函数，精确确定所述长导码组和所述短导码组的分界时间点，进而划分出每组内的两个段信号；
    第一计算模块，用于分别计算所述长导码组和所述短导码组内两段信号之间的复互相关函数；
    第二计算模块，用于分别计算所述长导码组和所述短导码组信号的功率谱；
    第三计算模块，用于计算所述长导码组和所述短导码组信号的功率谱差异，得到射频指纹，所述长导码组和所述短导码组信号的功率谱差异具体为：
    R FF(k)＝GDD(k)/GCC(k)＝P dd(k)/P cc(k)，其中GDD(k)为所述短导码组内两段信号之间的复互相关函数的傅里叶变换，GCC(k)为所述长导码组内两段信号之间的复互相关函数的傅里叶变换，P dd(k)和P cc(k)分别为所述短导码组和所述长导码组信号的功率谱，k＝0，1，...，N-1。
  8. 根据权利要求7所述的射频指纹提取的装置，其特征在于，所述第一计算模块计算而得的所述长导码组和所述短导码组内两段信号之间的复互相关函数具体为：
    Figure PCTCN2020110426-appb-100004
    Figure PCTCN2020110426-appb-100005
    其中
    Figure PCTCN2020110426-appb-100006
    表示求共轭操作，E[·]表示求期望运算，l＝0，1，...，N-1，
    接收信号
    y d1(n)＝s d1(n)*h(n)+v(n)
    y d2(n)＝s d2(n)*h(n)+v(n)
    y c1(n)＝s c1(n)*h(n)+v(n)
    y c2(n)＝s c2(n)*h(n)+v(n)
    其中d1和d2为短导码组内的两段符号，s d1(n)和s d2(n)为对应的发送信号；c1和c2为长导码组内的两段符号，s c1(n)和s c2(n)为对应的发送信号，n＝0，1，...，N-1，为采样点的序数；h(n)为多径信道，“*”表示线性卷积运算，v(n)为加性噪声；
    所述第二计算模块还用于对所述短导码组和所述长导码组内两段信号之间的复互相关函数做傅里叶变换，得到
    GDD(k)＝FFT[G d1d2(l)]＝P dd(k)|H(k)| 2
    和GCC(k)＝FFT[G c1c2(l)]＝P cc(k)|H(k)| 2
    当s d1(n)＝s d2(n)、s c1(n)＝s c2(n)时，有
    P dd(k)＝|FFT[s d1(n)]| 2＝|FFT[s d2(n)]| 2
    P cc(k)＝|FFT[s c1(n)]| 2＝|FFT[s c2(n)]| 2，
    H(k)＝FFT[h(n)]，k＝0，1，...，N-1。
  9. 一种无线接收机，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，其特征在于，所述处理器执行所述程序时实现权利要求1～6中任意一项所述射频指纹提取方法。
  10. 一种计算机可读存储介质，存储有计算机可执行指令，其特征在于，所述计算机可执行指令用于执行权利要求1～6中任意一项所述射频指纹提取方法。
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