Patch antenna, wireless device and polarization fingerprint authentication method and system of wireless device

Abstract

The invention relates to a patch antenna, wireless equipment and a polarization fingerprint authentication method and system of the wireless equipment. In the first aspect, the patch antenna is provided, the patch antenna is provided with injection grooves, the injection grooves are formed according to a set grooving scheme, the grooving schemes of different patch antennas are different, and the grooving schemes comprise the number of the injection grooves, the area where the injection grooves are located, the distance between the injection grooves and the center of the antenna and the length of the injection grooves. The second aspect provides a wireless device having the above patch antenna. The third aspect provides a polarization fingerprint authentication method for wireless equipment. The method comprises the following steps: sending a wireless signal through the wireless equipment; receiving the wireless signal and extracting a polarized fingerprint; matching the polarized fingerprint with a polarized fingerprint stored in a polarized fingerprint database; and authenticating the wireless equipment according to a matching result. By slotting the surface of the antenna and injecting the polarized fingerprint, the problem of insufficient fingerprint difference caused by hardware defects in the existing radio frequency fingerprint technology is solved.

Description

Technical Field

[0001] The present invention relates to a patch antenna, a wireless device, and a polarization fingerprint authentication method and system for the wireless device, belonging to the technical field of computers. Background Art

[0002] Physical layer authentication is a core technology for 6G's inherent security. It addresses communication security issues in wireless scenarios from the signal level. Radio Frequency Fingerprint (RFF) technology is a commonly used authentication method at the physical layer.

[0003] Radio Frequency Fingerprinting (RFF) is a device identification method based on the physical layer of wireless signals. It extracts physical-layer features from the signal transmitted by the transmitter, used to identify the device. Radio Frequency Fingerprinting (RFF) arises from random hardware defects introduced during the device manufacturing process. However, with the advancement of advanced RF front-end manufacturing technology, the scale of random hardware defects in the RF front-end is decreasing. Traditional RFFs exhibit relatively similar characteristics, thus reducing the device capacity of the identification system. Naturally generated RFFs cannot be customized by users and lack configurability. Furthermore, RFFs suffer from poor stability and complex data processing. These issues prevent RFF technology from meeting the required differentiation and stability requirements for large-scale applications. Intervention of RFF generation could effectively address these issues.

[0004] In recent years, researchers have proposed methods for artificially injecting RFF, such as by utilizing additional hardware, to overcome the aforementioned challenges. These methods aim to introduce random variations in the time and frequency domain characteristics of RF signals, such as I / Q imbalance or errors in the amplitude and phase of wireless signals.

[0005] Artificially injecting RFFs brings effective improvements, but because the physical features used to extract these RFFs are usually modulated to carry information, these schemes inevitably cause distortion to the modulated signal.

[0006] Artificially injecting RFFs brings effective improvements, but because the physical features used to extract these RFFs are usually modulated to carry information, these schemes inevitably cause distortion to the modulated signal. Summary of the Invention

[0007] To address the shortcomings of existing RFF fingerprint injection schemes for IoT authentication and improve the reliability and security of access authentication for large-scale IoT devices, this paper proposes a novel artificial polarization fingerprint injection (APFI) scheme. This scheme utilizes the polarization state of the radio frequency signal to construct a fingerprint, called a polarization fingerprint (PF). Unlike RFF, which is based on time-frequency characteristics, the polarization of the wireless signal does not carry modulation information and can therefore be extracted from the entire signal duration. Furthermore, its vector characteristics provide greater variability in the fingerprint. Since the polarization of the transmitted signal is primarily determined by the antenna structure, the key concept of this invention is to achieve fingerprint injection by creating differentiated, tiny grooves on each antenna surface without affecting the antenna's radiation performance. Compared to existing RFF fingerprint injection schemes, this method does not require additional hardware overhead on the transmitter side. This advantage makes the present invention universally applicable to IoT devices equipped with microstrip patch antennas and compatible with existing communication protocols.

[0008] The first aspect of the present invention provides a patch antenna, which has an injection slot. The injection slot is opened according to a set slotting scheme. Different patch antennas have different slotting schemes. The slotting scheme includes the number of injection slots, the area where the injection slots are located, the distance between the injection slots and the center of the antenna, and the length of the injection slots.

[0009] Furthermore, the injection groove is a rectangular groove.

[0010] A second aspect of the present invention provides a wireless device having the above-mentioned patch antenna.

[0011] A third aspect of the present invention provides a polarization fingerprint authentication method for a wireless device, the steps of which include:

[0012] sending a wireless signal via the wireless device;

[0013] receiving the wireless signal and extracting a polarization fingerprint;

[0014] matching the polarization fingerprint with polarization fingerprints stored in a polarization fingerprint database;

[0015] The wireless device is authenticated according to the matching result.

[0016] Furthermore, the matching results are evaluated using the difference index.

[0017] Furthermore, the false rejection rate and false recognition rate are used as performance evaluation indicators, and the threshold of the difference index is obtained through the false rejection rate and false recognition rate.

[0018] Furthermore, when the false rejection rate is equal to the false recognition rate, it is set as the optimal threshold of the difference index.

[0019] A fourth aspect of the present invention provides a polarization fingerprint authentication system for a wireless device, comprising:

[0020] A wireless device having the above patch antenna is used to transmit a wireless signal containing polarization fingerprint information;

[0021] A receiving device for receiving the wireless signal, comprising a fingerprint information extraction module for extracting the polarization fingerprint information;

[0022] a fingerprint matching module for matching the polarization fingerprint with polarization fingerprints stored in a polarization fingerprint database;

[0023] The authentication module is used to authenticate the wireless device according to the matching result.

[0024] Furthermore, the matching results are evaluated using the difference index.

[0025] Furthermore, the false rejection rate and false recognition rate are used as performance evaluation indicators, and the threshold of the difference index is obtained through the false rejection rate and false recognition rate.

[0026] The beneficial effects of the present invention are as follows:

[0027] 1. Artificial Polarization Fingerprint Injection (APFI)

[0028] Innovation: By slotting the antenna surface to inject a polarization fingerprint, this approach eliminates the hardware limitations of existing radio frequency fingerprinting (RFF) technology, resulting in insufficient fingerprint differentiation. This process generates a unique polarization fingerprint by changing the antenna polarization state, thereby increasing the device capacity and accuracy of the device authentication system.

[0029] Technical Problem Solved: In existing technologies, the diversity of device fingerprints has gradually decreased due to advances in manufacturing processes, resulting in insufficient device recognition capabilities in RF fingerprinting technology. This invention generates highly differentiated polarization fingerprints by controlling the slot parameters on the antenna surface.

[0030] 2. Utilization of Polarization Mode Dispersion (PMD) Effect

[0031] Innovative Technical Features: This invention utilizes the polarization mode dispersion (PMD) effect created by multiple slots on the antenna surface for the first time, enhancing the uniqueness and diversity of fingerprints at the device level rather than the channel level. The frequency correlation variation produced by the multiple slots results in significant differences in fingerprint performance at different frequencies, ensuring that each device's polarization fingerprint is unique across a wide frequency range.

[0032] Solving technical problems: With traditional radio frequency fingerprint technology, the fingerprint differences between devices are small, which is prone to recognition errors, especially in large-scale device authentication. The introduction of the PMD effect greatly increases the differences in polarization fingerprints.

[0033] 3. Physical layer authentication system based on polarization fingerprint

[0034] Innovative Components and Component Combinations: This paper proposes a physical-layer authentication system based on artificial polarization fingerprint injection, combining the polarization characteristics of radio frequency signals with physical-layer authentication algorithms. The system includes a polarization fingerprint injection module on the transmitter side, a fingerprint extraction module on the receiver side, and a fingerprint matching and authentication module. This system design eliminates the need for adding complex hardware to existing IoT devices, effectively improving the differentiation and security of device authentication.

[0035] New component combination: By combining polarization fingerprint injection with RF signal processing, a new physical layer authentication scheme is formed. Unlike existing cryptography-based authentication schemes, this invention does not rely on encryption methods with high computational overhead. Instead, it can achieve efficient authentication through simple antenna modifications. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 FIG. 4 is a surface current vector diagram of an antenna with multiple surface slots according to an embodiment of the present invention.

[0037] Figure 2 This is a data diagram showing the PMD phenomenon of the antenna polarization state in an embodiment of the present invention.

[0038] Figure 3 Schematic diagram of the original antenna design and surface grooves in an embodiment of the present invention.

[0039] Figure 4 Schematic diagram of the APFI system model in an embodiment of the present invention.

[0040] Figure 5 This is a data diagram of the difference in polarization fingerprints between the attacker and the attacked at different distances and rotation angles in an embodiment of the present invention.

[0041] Figure 6 This is a data diagram showing the impact of noise and sample size on fingerprints in an embodiment of the present invention.

[0042] Figure 7 Schematic diagram comparing the accuracy of the method of the present invention and the prior art. DETAILED DESCRIPTION

[0043] The present invention will be described in further detail below with reference to the accompanying drawings. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0044] The present invention selects a dual-slot circularly polarized patch antenna as a research object, but the present invention can also be used for other types of patch antennas.

[0045] According to antenna radiation theory, the corresponding vector potential ( Magnetic vector potential and The electric vector potential) can be obtained from the current density of the radiation source ( Current density and The magnetic current density) is obtained according to the integral relationship. Then the antenna radiation field ( Electric field and magnetic field). In terms of time-harmonic current, it can be expressed as:

[0046]

[0047] Where ω is the angular frequency, k 2 =ω 2 μ∈, μ and ∈ are the magnetic permeability and dielectric constant, respectively, and R is the distance from any point in the source to the observation point. Therefore, the effect of the surface slot on the antenna's polarization state can be replaced by its effect on the current density on the antenna surface. By performing vector decomposition on the electromagnetic field intensity, if the amplitudes of the two orthogonal electric field components and the phase difference between them remain constant, the polarization state can be represented by the Jones vector. The Jones vector is represented by two complex numbers that describe the amplitude and phase difference of the electromagnetic wave in two perpendicular directions, as shown in the following formula.

[0048]

[0049] Then the change of the slot design on the polarization state of the antenna was analyzed, and the polarization state results of different slot designs were obtained. The study showed that the change of slot parameters will significantly affect the polarization state of the antenna. Figure 1 and Figure 2 As shown in the figure, when there are multiple slots on the antenna surface, multiple current paths will be formed on the antenna surface. Each path will produce a different propagation delay due to different slot parameters, and the current complex amplitude of each path will also be different. As a result, the polarization state of the antenna will show frequency-related changes. This phenomenon is called PMD (Polarization Mode Dispersion). By utilizing this phenomenon, the difference in polarization fingerprints between different devices can be effectively increased, thereby providing effective support for the injection of polarization fingerprints into large-scale devices. Based on the above analysis, the work of injecting artificial polarization fingerprints into the antenna through slots is established. By controlling the slot parameters, the uniqueness of the injected polarization fingerprint can also be guaranteed.

[0050] In a first aspect, this embodiment discloses a patch antenna that uses a polarization fingerprint injection method to create surface slots. The APFI scheme uses the number of slots (N), the area (A) where the slots are located, the distance (D) between the slots and the antenna center, and the slot length (L) as key parameters. A quaternion array (n, a, d, l) composed of these parameters uniquely identifies the APFI scheme. Figure 3 The injection slots obtained by surface grooving in this embodiment are shown. The number of injection slots (N) is a positive integer. The area (A) where the injection slots are located mainly has the following value range A = {1, 2, 3, 4}. The distance between the injection slot and the antenna center (D) can be expressed as the set D = {d min ,d min +∈,…,d max -∈,d max}. Among them, d min and d max Respectively represent the closest and farthest effective distances between the injection slot and the antenna center. According to the structure of the antenna, this embodiment uses the WYUAN brand RD915M-TX-3DBI model antenna, whose d min The value is 12 mm, d max The value is 62 mm. ∈ represents the step size parameter related to the distance between the slot and the antenna center. It is worth noting that Figure 3 Among the four regions, d min and d max The values ​​of are the same, but in region 2, due to the presence of an antenna feed point, the distance values ​​of set D are missing. The length of the injection slot (L) can be expressed as the set in, It represents the maximum slot length that does not affect the antenna performance after determining the area parameter A and the distance parameter d. δ represents the step size parameter related to the slot length. Quantify and uniquely determine the AFPI scheme. In this embodiment, the injection slots obtained by surface grooving are rectangular injection slots with a slot width of 3δ. After confirming the AFPI scheme, the patch antenna is punched at the slot location according to the scheme.

[0051] At the transmitter, polarization fingerprint injection is achieved by creating slots on the antenna surface. By precisely controlling the parameters of the slotted AFPI scheme, the device's polarization fingerprint can be artificially injected. This process alters the current distribution on the antenna surface, thereby affecting the signal's polarization state, ensuring that each device has a unique polarization fingerprint in the wireless signal. Through this process, the polarization fingerprint is embedded in the signal and propagates along with it to the receiver.

[0052] For wireless devices, the corresponding polarization fingerprint can be extracted from the electromagnetic signal it transmits. In this embodiment, the receiving end uses an orthogonal dual-polarization antenna. According to the previous analysis, the polarization state is related to the frequency. The frequency range of the signal is f1, f2, ..., f n , then at frequency f k The repolarization state at can be expressed as

[0053]

[0054] According to the value of the complex polarization state of the signal at different frequencies, the polarization fingerprint of the antenna is expressed as:

[0055]

[0056] For different antenna devices, due to differences in hardware structure, even within the same frequency range, the complex polarization state values ​​at different frequency points vary, resulting in different corresponding polarization fingerprints. The extracted polarization fingerprint is represented by the Jones vector model, which includes the amplitude and phase information of the wireless signal. For antenna devices of the same model, their hardware differences usually come from natural hardware defects introduced during the generation process. As the device manufacturing process improves, the differences in polarization fingerprints caused by these defects gradually decrease, increasing the difficulty of device identification. By applying different APFI schemes, since the PMD effect is also frequency-dependent, the values ​​of the complex polarization state at different frequencies under different devices can be significantly changed, expanding the differences in polarization fingerprints and achieving the purpose of artificial polarization fingerprint injection.

[0057] The second aspect of this embodiment provides a polarization fingerprint authentication method, the process is as follows Figure 4 As shown, the transmitter has N patch antennas. An IoT device attempts to connect to the receiver. All transmitters in the communication network inject polarization fingerprints according to the APFI scheme described above. After legitimate devices are deployed, the receiver extracts the injected polarization fingerprints using the signals measured from the transmitters. The decision-making end classifies the polarization fingerprints of all devices and stores them in a database. The receiver then directly collects the polarization fingerprints of legitimate devices for authentication. If the result matches the legitimate device's identity, authentication succeeds; otherwise, authentication fails.

[0058] In order to improve the matching effect of polarization fingerprint, the present invention proposes a fingerprint difference evaluation index. The polarization fingerprint in the device can be expressed as R i =(p ri (f1),p ri (f2),…,p ri (f n )), and S i =(p si (f1),p si (f2),…,psi (f n )) represents the polarization fingerprint of the device used for comparison. Where n represents the dimension in frequency. The difference index between any two devices can be expressed as:

[0059]

[0060] This embodiment uses the difference index ((d(R i ,S i )) is used as a standard to measure different polarization fingerprints. The differences between the same polarization fingerprints and different polarization fingerprints under different signal-to-noise ratios (SNR) are calculated, and the false rejection rate and false recognition rate are used as performance evaluation indicators. The threshold of the difference index is calculated by the false rejection rate and false recognition rate. The false rejection rate (FRR) refers to the probability that the collected device polarization fingerprint is judged to be different from the template previously stored in the database during the authentication process. The specific judgment standard is that the difference index is greater than a given threshold ((d(R i ,S i )>thresld). False Accept Rate (FAR) refers to the probability that the polarization fingerprints of different devices collected during the authentication process are judged to be the same. The specific judgment standard is that the difference index is less than a given threshold ((d(R i ,S i )>thresld). When the false rejection rate is equal to the false recognition rate, the threshold is the optimal threshold. When the optimal threshold is obtained, the authentication accuracy is:

[0061] IR = [1-(FRR + FAR)] × 100%.

[0062] In order to evaluate the effect of the method of the present invention, the third aspect of the present invention provides the following multiple verification experiments and obtains corresponding experimental data.

[0063] 1. Safety verification experiment

[0064] In the security assessment of the identity authentication scheme of the present invention, the defense capabilities against forgery attacks and exhaustive attacks are analyzed. In a forgery attack, the attacker needs to know the antenna type and polarization fingerprint injection scheme of the device. Figure 5Experiments show that the difference in polarization fingerprints increases with increasing distance and rotation angle between the attacker and the target device. Even when the attacker is in the same location as the target device, differences persist. When the fingerprint difference exceeds 0.4, the attack success rate approaches 0%. For brute force attacks, since the attacker cannot obtain the polarization fingerprint of a legitimate device, it is difficult to successfully launch an attack using only the same device model. Therefore, this solution effectively prevents forgery and brute force attacks.

[0065] 2. Robustness and noise immunity verification experiment

[0066] In order to test the robustness and anti-interference performance of the artificial polarization fingerprint injection scheme, the present invention measures the fingerprint deviation under different signal-to-noise ratios and different sample numbers. Compared with the traditional RFF, the present invention can collect polarization fingerprint samples at any time during the communication process. According to the continuity of the polarization fingerprint, the average value is used to eliminate the influence of noise on the collected polarization fingerprint. Figure 6 As can be clearly seen in the figure, the deviation between the collected fingerprint and the original fingerprint decreases as the number of samples increases. In low signal-to-noise ratio conditions, the injected fingerprint achieves significant noise immunity by increasing the number of samples. However, this improvement has a ceiling as the number of samples increases. These results demonstrate that the polarization fingerprint injection scheme can extract robust features that are resistant to fingerprint instability caused by wireless signal fluctuations.

[0067] 3. Recognition Accuracy Verification Experiment

[0068] The present invention compares the proposed APFI, the original polarization fingerprint and the traditional method of using I / Q samples as fingerprints. The present invention uses four twice-slotted antennas in different positions, four once-slotted antennas in different positions and four non-slotted antennas as APFI sample sets. The original polarization fingerprint data uses 12 RD915M-TX-3DBI antennas, and the I / Q samples of these 12 antennas are also collected as traditional fingerprints. The comparison results are shown in the figure, and it can be seen that APFI has the best performance among all methods. In the case of low signal-to-noise ratio, the APFI scheme can still maintain a high accuracy rate. At a signal-to-noise ratio of 6dB, APFI still maintains 100% accuracy, while the original polarization fingerprint and I / Q samples are reduced to below 90%. This is because the fingerprint is more dispersed in the feature space through APFI, such as Figure 7 The results show that the proposed APFI scheme can achieve higher accuracy compared with the current technology.

[0069] While specific embodiments of the present invention have been disclosed for illustrative purposes, intended to facilitate understanding and implementation of the present invention, those skilled in the art will appreciate that various substitutions, variations, and modifications are possible without departing from the spirit and scope of the present invention and the appended claims. Therefore, the present invention should not be limited to the disclosure of the preferred embodiments, and the scope of protection claimed in the present invention shall be determined by the scope of the claims.

Claims

1. A patch antenna having an injection slot, wherein the injection slot is opened according to a set slotting scheme, and different patch antennas have different slotting schemes. The slotting scheme includes the number of injection slots, the area where the injection slots are located, the distance between the injection slots and the center of the antenna, and the length of the injection slots.

2. The patch antenna according to claim 1, wherein The injection groove is a rectangular groove.

3. A wireless device, characterized in that: A patch antenna according to claim 1 or 2.

4. A polarization fingerprint authentication method for a wireless device according to claim 3, comprising: sending a wireless signal via the wireless device; receiving the wireless signal and extracting a polarization fingerprint; matching the polarization fingerprint with polarization fingerprints stored in a polarization fingerprint database; The wireless device is authenticated according to the matching result.

5. The method according to claim 4, wherein: The matching results were evaluated using the difference metric.

6. The method according to claim 5, wherein: The false rejection rate and false recognition rate are used as performance evaluation indicators, and the threshold of the difference index is obtained through the false rejection rate and false recognition rate.

7. The method according to claim 5, wherein: When the false rejection rate is equal to the false recognition rate, it is set as the optimal threshold of the difference index.

8. A polarization fingerprint authentication system for a wireless device, comprising A wireless device having the patch antenna according to claim 1 or 2, used for transmitting a wireless signal containing polarization fingerprint information; A receiving device for receiving the wireless signal, comprising a fingerprint information extraction module for extracting the polarization fingerprint information; a fingerprint matching module for matching the polarization fingerprint with polarization fingerprints stored in a polarization fingerprint database; The authentication module is used to authenticate the wireless device according to the matching result.

9. The system according to claim 8, wherein: The matching results were evaluated using the difference metric.

10. The system according to claim 9, wherein: The false rejection rate and false recognition rate are used as performance evaluation indicators, and the threshold of the difference index is obtained through the false rejection rate and false recognition rate.

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