A ray tracing-based physical layer security performance evaluation method for urban private communications

Abstract

This invention discloses a method for evaluating the physical layer security performance of private communication in urban environments based on ray tracing. It primarily addresses the problem of inaccurate physical layer communication security performance evaluation in existing technologies. The implementation scheme involves: extracting the geometric and electromagnetic material characteristics of urban buildings; setting the geographical and electromagnetic information of the signal sender, receiver, and eavesdropper; simulating and calculating the predicted received power and small-scale fading characteristics at each point of the receiver and eavesdropper based on the dataset of building geometric and electromagnetic material characteristics and the geographical and electromagnetic information of the signal sender, receiver, and eavesdropper; and simulating and calculating the confidentiality performance of the entire area under noise-limited and noise / interference scenarios based on the received power and small-scale fading characteristics to obtain the probability of security interruption. This invention can achieve accurate prediction of the physical layer security performance of private communication scenarios in actual urban environments when the eavesdropper's channel state information is unknown, and can be used to optimize the confidentiality performance of urban private communication.

Description

Technical Field

[0001] This invention belongs to the field of communication technology, and in particular relates to a method for evaluating the physical layer security performance of urban private communication, which can be used for evaluating and optimizing the confidentiality performance of urban private communication. Background Technology

[0002] With the rapid adoption of wireless communication technology in modern life, an unprecedented amount of private information is being transmitted over wireless media. Due to the immutable openness of wireless channels, communication security has become a critical issue. To protect wireless communication by utilizing the characteristics of wireless channels, physical layer security, as a supplement to traditional cryptographic techniques, has been extensively studied. Scholar Wyner, in his pioneering work, introduced eavesdropping channel systems as a framework for physical layer security and defined confidentiality capacity as the maximum rate at which a message can be reliably sent to its intended recipient without being eavesdropped. Later, scholars Csiszár and... This result has been extended to broadcast channels carrying confidential messages. In recent years, numerous scholars have conducted extensive analyses of physical layer security in various communication scenarios. However, due to idealized and unrealistic assumptions, most research in this field is theory-driven. For example, many existing articles assume that the transmitter possesses perfect Channel State Information (CSI) to the intended receiver and the eavesdropper. In practical applications, external eavesdroppers naturally will not cooperate with the transmitter by sending CSI feedback, making it difficult for the transmitter to obtain the eavesdropper's CSI. Furthermore, many existing articles do not consider the actual real-world environment and radio wave propagation effects, equating path loss with powers of distance, and even ignoring shadow fading, rendering existing theoretical analyses inapplicable to practice.

[0003] Patent application CN201811075144.8 discloses a physical layer security optimization method based on heterogeneous wireless transmission mode scheduling. This method divides information transmission into three steps: data aggregation, transmission mode scheduling, and data forwarding. It adaptively designs corresponding transmission modes based on the availability of instantaneous eavesdropping channel state information and the estimated probability of a successful eavesdropping attempt, aiming to counter eavesdropping and improve information transmission confidentiality. However, this method focuses on network layer scheduling planning—specifically, how to formulate corresponding countermeasures once the eavesdropper's channel state information is known. Therefore, it cannot simulate and analyze the confidentiality of the current communication scenario when the eavesdropper's channel state information is unknown. Furthermore, since eavesdroppers are unlikely to actively send their received signal's channel state information to the private transmitter in real-world private communications, this method is difficult to apply to countering eavesdropping in real-world urban environments.

[0004] Patent application CN201310244665.2 discloses a method for predicting indoor three-dimensional spatial wireless signals based on a ray-tracing propagation model. This method calculates the electromagnetic propagation characteristics of indoor signals by hierarchically modeling the building and solving the corresponding mapping relationships of antennas on each floor. It also reduces computational complexity by using a database of wireless propagation loss parameters based on building materials, thus simplifying the calculation of ray tracing for indoor three-dimensional spatial wireless signals. However, because this method focuses on the electromagnetic calculation algorithm itself and does not consider the security requirements and practical application value of private communication in actual urban environments, it cannot directly help analyze the confidentiality and security performance of actual communications. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of the prior art by proposing a method for evaluating the physical layer security performance of urban private communication based on ray tracing, so as to achieve accurate coverage prediction of the physical layer security performance of private communication scenarios in actual urban environments when the channel state information of eavesdroppers is unknown.

[0006] The key technology of this invention is as follows: Using existing environmental and electromagnetic modeling data, a ray tracing algorithm is used to predict the received power of potential eavesdroppers throughout the entire area. This prediction is then substituted into the physical layer security calculation formula to obtain the confidentiality performance assessment result for a specified area. The implementation steps include the following:

[0007] (1) Obtain the vector data of buildings and material electromagnetic parameters of a specified city scene;

[0008] (2) Set the location and electromagnetic information of the information sender, receiver and eavesdropper according to actual needs;

[0009] (3) Based on the obtained modeling data and set parameter information, the received power prediction results for each receiving point are obtained through ray tracing simulation, and the small-scale fading characteristic parameters m and ω are fitted:

[0010] (3a) Set up three configuration files with different formats and store the geographic and electromagnetic information required for simulation analysis;

[0011] (3b) Analyze all ray paths of the signal from the transmitter Tx to the receiver Rx;

[0012] (3c) Calculate the total electric field at each receiving point based on the ray path obtained from step (3b).

[0013] (3d) Convert the total electric field calculated in step (3c) into the received power P at each receiving point. r And output it according to the format of the third configuration file;

[0014] (3e) Generate a small-scale fading simulation point set, simulate the received signal amplitude at each point, and fit the small-scale fading characteristic parameters m and ω.

[0015] (4) The received power P at each point obtained in step (3) r Substituting the small-scale fading characteristic parameters m and ω into the formulas for calculating the probability of security interruption in various communication scenarios, we obtain the corresponding security performance prediction results.

[0016] (4a) The received power P at each point r Substituting the small-scale fading characteristic parameters m and ω into the formula for calculating the probability of secure communication interruption in a noise-constrained communication scenario, the probability of secure communication interruption P is calculated. out1 ;

[0017] (4b) Derive the formula for calculating the probability of secure communication interruption in general communication scenarios with interference and noise, and calculate the received power P at each point. r Substituting the small-scale fading characteristic parameters m and ω into the formula, the probability of security breach P is calculated. out2 .

[0018] Compared with the prior art, the present invention has the following advantages:

[0019] Firstly, because the present invention obtains more accurate vector data of urban scene buildings and material electromagnetic medium parameters, the received power calculated by the present invention is more accurate than that of the prior art.

[0020] Secondly, since the present invention uses ray tracing simulation instead of actual measurement to obtain the received power, the cost of obtaining small-scale fading characteristic parameters is lower than that of the prior art.

[0021] Third, because the present invention calculates the probability of security interruption by using the accurate received power obtained through ray tracing simulation, the probability of security interruption calculated by the present invention is more accurate than the analysis results of the prior art that do not consider the actual environment.

[0022] Fourth, since this invention derives a general formula for calculating the probability of security interruption under the presence of interference and noise signals, it has a wider range of applications compared to existing technologies. Attached Figure Description

[0023] Figure 1 This is a flowchart illustrating the implementation of the present invention;

[0024] Figure 2 This is a schematic diagram of the interface for obtaining building vector data in an embodiment of the present invention;

[0025] Figure 3 This is a schematic diagram of the building data results extracted in an embodiment of the present invention;

[0026] Figure 4 This is a schematic diagram of the mirror method used in the embodiments of the present invention;

[0027] Figure 5 This is a graph showing the ray tracing power coverage prediction results in an embodiment of the present invention;

[0028] Figure 6 This is a graph showing the received power results at different frequency points obtained from actual measurements;

[0029] Figure 7 This is a comparison chart of the received power obtained from the simulation and the actual measured value of the received power in this invention;

[0030] Figure 8 This is a graph showing the simulation results of signal amplitude and probability distribution fitting under line-of-sight conditions according to the present invention.

[0031] Figure 9 This is a diagram showing the simulation results of signal amplitude and probability distribution fitting under non-line-of-sight conditions according to the present invention;

[0032] Figure 10 This is a simulation result of the security interruption probability assessment of the present invention in a Gaussian white noise-constrained scenario.

[0033] Figure 11 This is a simulation result diagram of the probability assessment of security interruption in a scenario where Gaussian white noise and interference signals coexist. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments.

[0035] This embodiment establishes a scheme for physical layer security performance assessment in a real urban environment. It mainly sets the location and electromagnetic information of the information sender, receiver, and eavesdropper according to actual needs. By acquiring building vector data and material electromagnetic medium parameter data of a specified urban scene, it calls the ray tracing algorithm to calculate the average received power of the receiving point set in the specified area. Then, by using a small-area fine point set subdivision method, it obtains the small-scale parameter features of Nakagmi-m through ray tracing simulation fitting, and constructs a received power probability distribution model. The communication scene is divided into two parts according to the presence or absence of interference signals, and their confidentiality performance expressions are derived separately. Finally, based on the received power dataset and small-scale fading parameter dataset obtained from the simulation, the accurate physical layer security performance index of the specified area is calculated.

[0036] Reference Figure 1 The implementation steps of this embodiment include the following:

[0037] Step 1: Obtain the building vector data and material electromagnetic medium parameters for the specified city scene.

[0038] 1.1) Obtain building vector data:

[0039] Methods for obtaining building vector data include acquiring it from the open-source map editing website OpenStreetMap, from the map data platform Google Earth, and using laser point cloud scanning modeling. This step uses, but is not limited to, acquiring data from the OpenStreetMap website. OpenStreetMap (OSM) is an online map collaboration project whose goal is to create a world map that is free to edit and open to all. OSM data is open source and can be freely downloaded and used. On OpenStreetMap, users can freely select locations of interest based on satellite maps, delineate points to form lines and polygons, and export the latitude and longitude coordinates of each point. The interface is shown below. Figure 2 As shown in the image. By marking building attributes on the map, the latitude and longitude coordinates of buildings in a specified area can be exported. After processing, the final building projection is obtained, as shown in the image. Figure 3 As shown.

[0040] 1.2) Obtain the electromagnetic medium parameters of the material:

[0041] Methods for obtaining electromagnetic dielectric parameters of materials include retrieving them from ITU recommendations and actual measurements. This step uses, but is not limited to, obtaining them from ITU recommendations. ITU recommendations are a series of models and parameter databases published by the International Telecommunication Union for the development of the electronic information field. They cover almost all existing communication technologies, including electromagnetic wave propagation and signal processing. Consulting ITU recommendations can quickly retrieve the permeability and dielectric constant of common materials in urban environments, such as building bricks and street trees.

[0042] Step 2: Set the location and electromagnetic information of the information sender, receiver, and eavesdropper according to actual needs.

[0043] The electromagnetic information includes antenna gain, signal wavelength, initial transmit power, initial transmit electric field, number of antennas, and antenna pattern.

[0044] The geographical location refers to the latitude and longitude or relative coordinates of the current location of the transmitter, receiver, and eavesdropper.

[0045] The location and electromagnetic information set in this step includes:

[0046] Set the geographical location of the transmitter and the transmit antenna gain G. t Transmitted signal wavelength λ, initial power P t The initial electric field E0, the number of transmitting antennas, and the transmitting antenna pattern;

[0047] Set the receiver's geographical location and the receiving antenna gain G. rThe number of receiving antennas and their radiation patterns;

[0048] Set the possible geographical locations of the eavesdropper and the eavesdropping antenna gain G. e The number of eavesdropping antennas and their radiation patterns.

[0049] Step 3: Based on the acquired modeling data and set parameter information, obtain the received power prediction results for each receiving point through ray tracing simulation, and fit the small-scale fading characteristic parameters m and ω.

[0050] 3.1) Set up three configuration files with different formats and store the geographic and electromagnetic information required for simulation analysis:

[0051] Set up three configuration files with different formats. The first configuration file is in the format of "variable name + value", the second configuration file is in the format of "longitude + latitude + altitude" or "relative coordinate X + relative coordinate Y + relative coordinate Z", and the third configuration file is in the format of "longitude + latitude + altitude + received power" or "relative coordinate X + relative coordinate Y + relative coordinate Z + received power".

[0052] Set the ray limit number N+M+L, reflection weight N, diffraction weight M, and transmission weight L for the ray tracing algorithm, and write them together with the electromagnetic information set in step 2 into the first configuration file. Then write the position information set in step 2 into the second configuration file.

[0053] 3.2) Treat each building in the building vector data obtained in step 1 as a polygonal prism, store the coordinates of each point on the horizontal polygon of each building and its vertical height, and combine the receiving point location information provided in the second configuration file to solve the direct, reflected, and diffracted paths that exist from the transmitting point Tx to each receiving point Rx:

[0054] 3.2.1) Solving for the path of the direct ray:

[0055] First, determine building obstruction on the line connecting the transmitter Tx and the receiver Rx:

[0056] If there is no obstruction, then Tx and Rx satisfy the line-of-sight condition, and the line connecting Tx and Rx is the direct path.

[0057] If there is occlusion, then Tx and Rx satisfy the non-line-of-sight condition and there is no direct path. Filter out the building plane that blocks the line connecting Tx and Rx, and perform the reflection path solution in 3.2.2) and the diffraction path solution in 3.2.3).

[0058] 3.2.2) Solving for the reflected ray path:

[0059] like Figure 4As shown in (a), the path of the reflected ray is solved according to the following steps:

[0060] The planes of buildings that block the rays are summarized into a set of mirror planes W. First, the first-order mirror point Tx1 of Tx relative to its nearest mirror plane W1 is determined. Then, the second-order mirror point Tx2 of the first-order mirror point Tx1 relative to its nearest self-defined mirror plane W2 is determined. The emission source Tx is connected to the first-order mirror point Tx1. The intersection of this line with plane W1 is the first-order reflection point P1.

[0061] Connect the second-order mirror point Tx2 with the receiving point Rx. The intersection of this line and the plane W2 is the second-order reflection point P2.

[0062] By analogy, we obtain multi-order reflection points Pn. Connecting Tx, each order reflection point Pn, and Rx, the resulting line is the path of the reflected ray.

[0063] 3.2.3) Solving for the path of the diffracted ray:

[0064] like Figure 4 As shown in (b), the emission source Tx is rotated around the vertical edge of the blocking plane W to form a hollow circle. Then, the true position of the first-order diffraction point D is found on the vertical edge, so that the line connecting the receiving point Rx and D intersects the boundary of the hollow circle. This process is repeated to obtain multiple diffraction points. The line connecting the emission source Tx, each diffraction point, and the receiving point Rx is the path of the diffraction ray.

[0065] 3.3) Extract the following parameters required for electromagnetic calculations from the ray path obtained in step 3.2):

[0066] Record the total number of reflections n and the total number of diffractions m that occur during the process of the ray from Tx to Rx;

[0067] Based on the elevation angle θ of the ray path relative to the transmitting antenna t and roll angle Extract the normalized direction factor of the transmitting antenna

[0068] Based on the elevation angle θ of the ray path relative to the receiving antenna r and roll angle Extracting the normalized direction factor of the receiving antenna

[0069] 3.4) Calculate the dihedral reflection coefficient at the h-th reflection based on the material electromagnetic medium parameters obtained in step (1). The calculation formula is as follows:

[0070]

[0071] in, Let them represent the unit vectors of the incident and reflected rays under parallel polarization in the ray base coordinates, respectively. Let represent the unit vectors of the incident and reflected rays under vertical polarization in the ray base coordinates, respectively. Represents the parallel polarization reflection coefficient. Represents the vertical polarization reflection coefficient. μ represents the intrinsic impedance of the i-th medium. i ε represents the permeability of the i-th medium. i Let represent the dielectric constant of the i-th medium, where i = 1, 2.

[0072] 3.5) Calculate the diffraction coefficient for the j-th diffraction based on the material electromagnetic medium parameters obtained in step (1).

[0073] Calculate the parallel polarization reflection coefficient D || :

[0074]

[0075] Calculate the vertical polarization reflection coefficient D ⊥ :

[0076]

[0077] Where n = θ e / π,θ e Let β0 represent the exterior angle of the diffraction wedge, k represent the wave number, and β0 be the angle between the incident ray and the diffraction edge. Indicates the angle of incidence, Indicates the diffraction angle; F(·), a ± (·) represents two different transition functions, and their expressions are as follows:

[0078]

[0079]

[0080] In the formula N ± The smallest integer that satisfies the following equation:

[0081] L is a distance parameter, which is related to the type of wave, and is expressed as follows:

[0082]

[0083] Based on the parallel polarization reflection coefficient D || and vertical polarization reflection coefficient D ⊥ Calculate the diffraction coefficient

[0084]

[0085] in, Let them represent the unit vectors of the incident ray and the diffracted ray under parallel polarization in the ray base coordinates, respectively. These represent the unit vectors of the incident ray and the diffracted ray under vertical polarization in the ray base coordinates, respectively.

[0086] 3.6) Calculate the diffusion factor A of the reflected field. s1 and the diffusion factor A of the diffracted field s2 :

[0087]

[0088] Where r1 represents the distance from the incident point to the reflection point, and r2 represents the distance from the reflection point to the exit point;

[0089] s1 represents the distance from the incident point to the diffraction point, and s2 represents the distance from the diffraction point to the exit point.

[0090] 3.7) Calculate the electric field of the signal reaching the receiving antenna after passing through the i-th ray.

[0091] 3.7.1) Based on the initial electric field of the transmitted signal Calculate the radiation field from the emission point to the first node.

[0092]

[0093] Where k is the wave number, and r0 is the distance from the launch point to the first node. This represents the normalized directivity coefficient of the transmitting antenna;

[0094] 3.7.2) Based on the radiation field Calculate the electric field of the i-th ray path reaching the receiving antenna.

[0095] If the ray path is a line-of-sight path, then the first node is the receiving point, based on the normalized directivity of the receiving antenna. The electric field at the receiving antenna along the i-th ray path is calculated as follows:

[0096]

[0097] If the ray path is a non-line-of-sight path, then the electric field at the receiving point reached by the i-th ray path is:

[0098]

[0099] In the formula, n is the total number of reflections, m is the total number of diffractions, and A sr is the diffusion factor after reflection and diffraction. q It represents the distance from the q-th ray node to the (q+1)-th node.

[0100] 3.8) The receiving electric field of each ray path The total electric field at the receiving point is obtained by superimposing the vectors.

[0101]

[0102] Where I represents the total number of ray paths generated by the signal propagating from the emission point Tx to the receiving point Rx;

[0103] 3.9) Calculate the total electric field from step 3.8). Converted into received power P at each receiving point r :

[0104]

[0105] In the formula, P t G represents the antenna radiated power. t and G r Here, λ represents the gain of the transmitting antenna and the receiving antenna, respectively, and λ is the operating wavelength of the transmitting antenna.

[0106] 3.10) Generate a small-scale fading simulation point set, simulate the received signal amplitude at each point, and fit the small-scale fading characteristic parameters m and ω:

[0107] In order to analyze signal fading in real-world scenarios, this invention defines a square centered on the location of each eavesdropper for both line-of-sight and non-line-of-sight scenarios. The side length of this square is 10 times the wavelength of the transmitted signal. Within this square, 5000 points are equally spaced as simulation points, and the position information of these points is written into a second configuration file.

[0108] Repeat steps 3.3) to 3.9) to obtain the received signal amplitude α at each simulation point at a frequency of 2.4 GHz. Assuming that the received signal amplitude α conforms to a Nakagami-m distribution, the Nakagami-m distribution that best matches the simulation data is obtained by fitting using the least squares method. From this distribution, the shape parameter m and the scale parameter ω are obtained. The expression for the Nakagami-m distribution is as follows:

[0109]

[0110] Step 4, calculate the received power P at each point obtained in step (3). r Substituting the small-scale fading characteristic parameters m and ω into the formulas for calculating the probability of security interruption in various communication scenarios, we obtain the corresponding security performance prediction results.

[0111] 4.1) Based on the received power P at each point r The probability of security breach P is calculated using the small-scale fading characteristic parameters m and ω. out1 :

[0112] 4.1.1) Calculate the probability density of the signal-to-noise ratio of the received signals by Bob (the receiver) and Eve (the eavesdropper). and

[0113] Construct a set of N A Alice and N, the transmitters of the antennas B Bob and N are the legitimate receivers for the antennas. E A MIMO eavesdropping channel model consisting of two antennas, Alice-Bob and Alice-Eve, is constructed. It is assumed that both the main channel Alice-Bob and the eavesdropping channel Alice-Eve experience quasi-static Nakagami-m fading with a fading parameter of m. When only Gaussian white noise is considered, the signal y received by the legitimate receiver is... B The signal received by Eve, the illegal eavesdropper E They are represented as follows:

[0114]

[0115] Where P0 represents the initial power of the message signal, This represents a unit power information symbol, where P0 is the transmit power. It is the channel matrix from the transmitter Alice to the legitimate receiver Bob. This represents Gaussian white noise with an average power of N0. It is the channel matrix from the transmitter Alice to the legitimate receiver Bob. This represents Gaussian white noise with an average power of N0.

[0116] Assuming the channels between different antennas are uncorrelated, and that both the legitimate receiver Bob and the eavesdropping receiver Eve use maximum ratio combining technology via L... AB =N A ×N B and L AE =N A ×N E The signal-to-noise ratio γ of Bob, a legitimate receiver at a diversity path, is received by an independent and identically distributed diversity path. B The signal-to-noise ratio γ of Eve and the eavesdropping device E They are represented as follows:

[0117]

[0118] in, and These are the total signal power received by Bob and Eve, respectively. and These represent the signal power received by Bob and Eve on a certain diversity path, respectively. and All satisfy the Gamma distribution;

[0119] Based on γ B and γ E The expression for γ is obtained by applying the probability density transformation formula for composite variables. B probability density and γ E probability density:

[0120]

[0121] Where m is the shape parameter obtained from the fitting in step 3, ω B =P AB / N0 indicates that the average power P of the message signal received by Bob, the legitimate receiver, is... AB The ratio of the noise power N0 to the noise power N0, ω E =P AE / N0 indicates the average power P of the message signal received by Eve at the eavesdropping end. AE The ratio of the noise power N0;

[0122] 4.1.2) Based on the derivation in step 4.1.1), and Calculate the probability of security breach P out1 :

[0123]

[0124] 4.2) Based on the received power P r The derivation of the small-scale fading characteristic parameters m and ω to determine the probability of secure communication interruption P in scenarios with interference and noise. out2 :

[0125] 4.2.1) Calculate the signal-to-interference-plus-noise ratio probability density of the received signals for Bob (the receiver) and Eve (the eavesdropper). and

[0126]

[0127] First, for the eavesdropping channel model where other signals interfere with Bob and Eve, the signal y received by the legitimate receiver is... B The signal received by Eve, the illegal eavesdropper E They are represented as follows:

[0128]

[0129] Among them, P I Indicates the initial power of the interference signal. and These are the channel matrices between the interfering signal source and Bob and Eve, respectively;

[0130] Next, based on y B and y E The expression is used to derive Bob's signal-to-interference-plus-noise ratio λ. B The signal-to-interference-plus-noise ratio λ of Eve E :

[0131]

[0132] Where, L IB =N I ×N B L represents the diversity path from the interfering signal to the legitimate receiver Bob. IE =N I ×N E This represents the diversity path from the interference signal to Eve, the eavesdropping device. and These represent the total received interference signal power at Bob and Eve, respectively. and These represent the signal power received by the interfering signal source on a certain diversity path of Bob and Eve, respectively.

[0133] Then, based on λ B and λ E The expression yields λ B probability density and λ E probability density

[0134] In the formula, ω IB =P IB / N0 indicates that Bob, the legitimate receiver, received the average power P of the interference signal. IB The ratio of the noise power N0 to the noise power N0, ω IE =P IE / N0 indicates the average power P of the interference signal received by Eve at the eavesdropping terminal. IE The ratio of ω to the noise power N0 AB =P AB / N0 indicates that the average power P of the message signal received by Bob, the legitimate receiver, is... AB The ratio of the noise power N0 to the noise power N0, ω AE =P AE / N0 indicates the average power P of the message signal received by Eve at the eavesdropping end. AE The ratio of the noise power N0;

[0135] 4.2.2) The result derived from step 4.2.1) and The expression calculates the probability P of a security breach. out2 :

[0136]

[0137] Where C1, C2, C3, and C4 represent four different transition functions, and their calculation formulas are as follows:

[0138]

[0139] In the formula, R th This indicates the threshold for security breach. Represents a binary Meijer G series;

[0140] 4.2.3) Set the confidentiality interruption threshold R p According to the received power P at each point obtained in step (3) r Calculate the secrecy interruption probability P using the small-scale fading characteristic parameter m. out2 Assess the security performance of the physical layer:

[0141] When the probability of confidentiality being interrupted is P out2 Greater than R p At this time, the probability of the message being leaked is relatively high, and the sending of private information should be reduced or stopped.

[0142] When the probability of confidentiality being interrupted is P out2 Less than or equal to R p At this point, the probability of the message being leaked is low, and normal private communication can be carried out. Thus, the security performance assessment of the physical layer of urban private communication is completed.

[0143] The effects of this invention can be further illustrated by the following simulation experiments:

[0144] I. Simulation Conditions

[0145] Based on step one, obtain the building vector data and electromagnetic medium parameters of common materials of Xi'an University of Electronic Science and Technology. Based on step two, set the location information and electromagnetic information of the information sender, receiver and eavesdropper.

[0146] II. Simulation Content

[0147] Simulation 1: Under the above simulation conditions, coverage prediction simulation of the received signal power in a specified area is performed using steps 3.3) to 3.9) of this invention. The results are as follows: Figure 5As shown, the horizontal and vertical axes represent two-dimensional projections in a relative coordinate system, with units of meters. The gray-brown polygons represent buildings in the area, and the colors represent the strength of the received power at that point, with yellow being the strongest and blue the weakest, with units of dBm. Simulation data shows that the calculation method proposed in this invention can take into account the direct, reflection, and diffraction effects that occur during the propagation of electromagnetic waves.

[0148] Simulation 2: The received power of continuous wave at 2GHz and 4GHz was measured respectively, and the results are as follows. Figure 6 As shown, where Figure 6 (a) represents the measured results at 2GHz. Figure 6 (b) shows the measured results at 4GHz. Under the above simulation conditions, the simulated received power values ​​at 2GHz and 4GHz obtained from steps 3.3) to 3.9) of this invention are compared with the measured data, and the results are as follows. Figure 7 As shown, where, Figure 7 (a) Comparison of simulated and measured values ​​of continuous wave at 2 GHz receiving power. Figure 7 (b) shows the comparison between simulated and measured values ​​of continuous wave at 4 GHz receiving power. Figure 7 The comparison results show that the root mean square error of the present invention is no higher than 6.5dB, which indicates high accuracy.

[0149] Simulation 3: Under the above simulation conditions, the amplitude fluctuation of the received signal at each line-of-sight receiving point at a frequency of 2.4 GHz was simulated using step 3.10 of this invention. The results are as follows: Figure 8 As shown in (a), the small-scale fading characteristics at line-of-sight are obtained by fitting the amplitude fluctuation of the received signal. These characteristics are then compared with the theoretical model, and the results are as follows: Figure 8 As shown in (b), from Figure 8 The comparison results show that the line-of-sight small-scale fading feature fitting method proposed in this invention matches the theoretical model well.

[0150] Simulation 4: Under the above simulation conditions, the amplitude fluctuation of the received signal at each non-line-of-sight receiving point at 2.4 GHz was simulated using step 3.10 of this invention. The results are as follows: Figure 9 As shown in (a), the small-scale fading characteristics under non-line-of-sight conditions are obtained by fitting the amplitude fluctuation of the received signal. These characteristics are then compared with the theoretical model, and the results are as follows: Figure 9 As shown in (b), from Figure 9 The comparison results show that the non-line-of-sight small-scale fading feature fitting method proposed in this invention matches the theoretical model well.

[0151] Simulation 5: Under the above simulation conditions, the secrecy interruption probability P, considering only Gaussian white noise, is calculated using step 4.1) of this invention. out1 The result is as follows Figure 10 As shown. Figure 10 (a) represents the number of antennas N of the transmitting source. A Set to 1, the number of antennas N on the receiver B Set to 1, the number of antennas N for the eavesdropping party E Set to 1, security interruption threshold R th Prediction results of the probability of security interruption when the value is set to 5 and the noise power N0 is set to -80dBm; Figure 10 (b) represents the number of antennas N of the transmitting source. A Set to 1, the number of antennas N on the receiver B Set to 1, the number of antennas N for the eavesdropping party E Set to 3, confidentiality interruption threshold R th Prediction results of the probability of security breach when the value is set to 5 and the noise power N0 is set to -80dBm. From... Figure 10 The comparison results show that increasing the number of antennas used by the eavesdropper significantly increases the probability of security breaches.

[0152] Simulation 6: Under the above simulation conditions, the probability of security breach P in a general scenario considering Gaussian white noise and interference is calculated using step 4.2) of this invention. out2 The result is as follows Figure 11 As shown. Wherein:

[0153] Figure 11 (a) represents the number of antennas N of the transmitting source. A Set to 3, the number of antennas N on the receiver B Set to 3, the number of antennas N of the eavesdropping party E Set to 3, confidentiality interruption threshold R th The probability of security interruption in a designated area when the signal strength is 1, the noise power N0 is -80dBm, and the interference signal power is 0.1 times the transmitted signal power;

[0154] Figure 11 (b) represents the number of antennas N of the transmitting source. A Set to 3, the number of antennas N on the receiver B Set to 3, the number of antennas N of the eavesdropping party E Set to 3, confidentiality interruption threshold R th The probability of security interruption in a designated area when the signal strength is 1, the noise power N0 is -80dBm, and the interference signal power is 0.5 times the transmitted signal power.

[0155] from Figure 11 The comparison results show that when the interference signal causes more interference to the legitimate receiver than to the eavesdropper, the probability of security breach will increase significantly.

[0156] The above description is merely a specific example of the present invention and does not constitute any limitation on the present invention. Obviously, those skilled in the art, after understanding the content and principles of the present invention, may make various modifications and changes in form and details without departing from the principles and structure of the invention. However, these modifications and changes based on the ideas of the present invention are still within the scope of protection of the claims of the present invention.

[0157] It should be noted that the step numbers in the specification and claims of this invention are only for the purpose of clearly describing the embodiments of this invention and facilitating understanding, and their order is not limited.

Claims

1. A method for evaluating the physical layer security performance of urban private communication based on ray tracing, characterized in that, Including the following: (1) Obtain the vector data of buildings and material electromagnetic parameters of a specified city scene; (2) Set the location and electromagnetic information of the information sender, receiver and eavesdropper according to actual needs; (3) Based on the obtained modeling data and set parameter information, the received power prediction results for each receiving point are obtained through ray tracing simulation, and the small-scale fading characteristic parameters m and ω are fitted: (3a) Set up three configuration files with different formats and store the geographic and electromagnetic information required for simulation analysis; (3b) Analyze all ray paths of the signal from the transmitter Tx to the receiver Rx; (3c) Calculate the total electric field at each receiving point based on the ray path obtained from step (3b). (3d) Convert the total electric field calculated in step (3c) into the received power P at each receiving point. r And output it according to the format of the third configuration file; (3e) Generate a small-scale fading simulation point set, simulate the received signal amplitude at each point, and fit the small-scale fading characteristic parameters m and ω. (4) The received power P at each point obtained in step (3) r Substituting the small-scale fading characteristic parameters m and ω into the formulas for calculating the probability of security interruption in various communication scenarios, we obtain the corresponding security performance prediction results. (4a) The received power P at each point r Substituting the small-scale fading characteristic parameters m and ω into the formula for calculating the probability of secure communication interruption in a noise-constrained communication scenario, the probability of secure communication interruption P is calculated. out1 ; (4b) Derive the formula for calculating the probability of secure communication interruption in general communication scenarios with interference and noise, and calculate the received power P at each point. r Substituting the small-scale fading characteristic parameters m and ω into the formula, the probability of secrecy interruption P is calculated. out2 The implementation steps include the following: (4b1) Derive the signal-to-interference-plus-noise ratio λ of the message signal received by the receiver. B probability density According to the received power P of the message signal received by the receiver AB Gaussian white noise N0, the power P of the interference signal received by the receiver. IB The probability formula for composite variables is derived from... probability density The expression is as follows: Where m represents the shape parameter of the Nakagami-m distribution, ω IB This indicates the signal-to-noise ratio (SNR) of the interference signal received by the receiver. ω AB L represents the signal-to-noise ratio of the message signal received by the receiver. IB L represents the product of the number of interfering antennas and the number of receiving antennas. AB R represents the product of the number of transmit antennas and the number of receive antennas. th This represents the secrecy breach threshold, and Γ(·) represents the Gamma function. Represents the number of combinations; (4b2) Derive the signal-to-interference-plus-noise ratio λ of the message signal received by the eavesdropper. E Cumulative probability density According to the received power P of the message signal received by the eavesdropping party AE Gaussian white noise N0, the power P of the interference signal received by the receiver. IE The probability formula for composite variables is derived from... Cumulative probability density The expression is as follows: Where, ω AE ω represents the signal-to-noise ratio of the message signal received by the eavesdropping party. IE L represents the signal-to-noise ratio of the interference signal received by the eavesdropping party. AE L represents the product of the number of transmitting antennas and the number of eavesdropping antennas. IE This represents the product of the number of jamming antennas and the number of eavesdropping antennas; (4b3) Through probability density and cumulative probability density Derivation of the probability of security breach P out2 The following calculation formula: Where C1, C2, C3, and C4 represent four different transition functions, and their calculation formulas are as follows: In the formula, m represents the shape parameter of the Nakagami-m distribution, ω AB ω represents the signal-to-noise ratio of the message signal received by the receiver. IE ω represents the signal-to-noise ratio of the interference signal received by the eavesdropping party. IB ω represents the signal-to-noise ratio of the interference signal received by the receiver. AE L represents the signal-to-noise ratio of the message signal received by the eavesdropping party. IB L represents the product of the number of interfering antennas and the number of receiving antennas. AE L represents the product of the number of transmitting antennas and the number of eavesdropping antennas. IE R represents the product of the number of jamming antennas and the number of eavesdropping antennas. th This represents the secrecy breach threshold, and Γ(·) represents the Gamma function. Represents the number of combinations. This represents a binary Meijer G series.

2. The method according to claim 1, characterized in that... : In step (1), the building vector data and material electromagnetic medium parameters of the specified urban scene are obtained by downloading urban environmental geometric feature modeling files from publicly available map websites at home and abroad, and obtaining building vector data through parsing; and obtaining material electromagnetic medium parameters by looking up tables in ITU recommendations. In step (2), the location and electromagnetic information of the information sender, receiver, and eavesdropper are set according to actual needs. The information is set as follows: Set the geographical location of the transmitter and the transmit antenna gain G. t Transmitted signal wavelength λ, initial power P t The initial electric field E0, the number of transmitting antennas, and the transmitting antenna pattern; Set the receiver's geographical location and the receiving antenna gain G. r The number of receiving antennas and their radiation patterns; Set the possible geographical locations of the eavesdropper and the eavesdropping antenna gain G. e The number of eavesdropping antennas and their radiation patterns; The geographical location refers to the latitude and longitude or relative coordinates of the transmitter, receiver, and eavesdropper.

3. The method according to claim 1, characterized in that, Step (3a) involves setting up three configuration files with different formats to store the geographic and electromagnetic information required for simulation analysis. The steps include the following: (3a1) Set up three configuration files with different formats. The first configuration file is in the format of "variable name + value", the second configuration file is in the format of "longitude + latitude + altitude" or "relative coordinate X + relative coordinate Y + relative coordinate Z", and the third configuration file is in the format of "longitude + latitude + altitude + received power" or "relative coordinate X + relative coordinate Y + relative coordinate Z + received power". (3a2) Set the ray limit number N+M+L, reflection weight N, diffraction weight M, and transmission weight L of the ray tracing algorithm, and write them together with the electromagnetic information set in step (2) into the first configuration file, and write the position information set in step (2) into the second configuration file.

4. The method according to claim 1, characterized in that, Step (3b) analyzes all ray paths of the signal from the transmitter Tx to the receiver Rx. The steps include the following: (3b1) Treat each building in the building vector data obtained in step (1) as a polygonal cylinder, store the coordinates of each point of the horizontal polygon of each building and the vertical height, and combine the receiving point location information provided by the second configuration file to solve the direct, reflected and diffracted paths that exist in the process of going from the transmitting point to each receiving point: (3b2) Solving the path of the direct ray: First, determine the building obstruction of the line connecting the emitting source Tx and the receiving point Rx: If there is no obstruction, then Tx and Rx satisfy the line-of-sight condition, and the line connecting Tx and Rx is the direct path. If occlusion exists, then Tx and Rx satisfy the non-line-of-sight condition, and there is no direct path. Filter out the building planes that block the line connecting Tx and Rx, and execute steps (3b3) and (3b4): (3b3) Solving the reflected ray path: The building planes that block the ray are grouped into a set of mirror planes W. First, determine the first-order mirror point Tx1 of Tx relative to its nearest mirror plane W1. Then, determine the second-order mirror point Tx2 of the first-order mirror point Tx1 relative to its nearest self-defined mirror plane W2. Connect the emitting source Tx to the first-order mirror point Tx1 with a straight line; the intersection of this line with plane W1 is the first-order reflection point P1. Connect the second-order mirror point Tx2 to the receiving point Rx; the intersection of this line with plane W2 is the second-order reflection point P2. This process is repeated to obtain multiple-order reflection points Pn. The line connecting Tx, each-order reflection point, and Rx is the reflected ray path. (3b4) Solving the diffraction ray path: Rotate the emission source Tx around the vertical edge of the blocking plane W to form a hollow circle, and then find the true position of the first-order diffraction point D on the vertical edge, so that the line connecting the receiving point Rx and D intersects the boundary of the hollow circle. Repeat this process to obtain multiple-order diffraction points. The line connecting the emission source Tx, each order diffraction point, and the receiving point Rx is the diffraction ray path.

5. The method according to claim 1, characterized in that, In step (3c), the total electric field at each receiving point is calculated. The implementation steps include the following: (3c1) The total number of reflections n and the total number of diffractions m during the ray's journey from Tx to Rx are obtained analytically. Based on the elevation angle θ of the ray path relative to the transmitting antenna... t and roll angle Extract the normalized direction factor of the transmitting antenna Based on the elevation angle θ of the ray path relative to the receiving antenna r and roll angle Extracting the normalized direction factor of the receiving antenna (3c2) Calculate the dihedral reflection coefficient at the h-th reflection based on the material electromagnetic medium parameters obtained in step (1). and the diffraction coefficient at the lth diffraction. The diffusion factor A of the reflected field is calculated based on the location information of each ray node. s1 and the diffusion factor A of the diffracted field s2 ; (3c3) Read the initial electric field E0 of the transmitted signal from the first configuration file, and according to the diffusion factor A s The radiation field of the transmitted signal at the first node is calculated using the distance r0 from the source Tx to the first node. The received electric field is calculated as follows: starting from the emission source Tx, passing through the i-th ray path, and reaching the receiving point Rx. (3c4) The total electric field at the receiving point is obtained by superimposing the received electric field vectors of each ray path. Where I represents the total number of ray paths generated when the signal propagates from the emission point Tx to the receiving point Rx. Let Rx represent the received electric field that travels from the emission source Tx through the i-th ray path to the receiving point Rx.

6. The method according to claim 5, characterized in that, In step (3d), the total electric field is converted into the received power at each receiving point. The steps include the following: (3d1) Read the first configuration file to obtain the initial power P of the transmitted signal. t Transmit antenna gain G t Receiver antenna gain G r The transmitted signal wavelength λ and the initial intensity of the transmitted electric field E0; (3d2) Using the parameters read in step (3d1), combined with the total received electric field obtained in step (3c) The received power P at each receiving point was calculated. r ; Among them, G t G represents the transmit antenna gain. r λ represents the receiving antenna gain, and λ represents the transmitted signal wavelength. E0 represents the scalar value of the initial intensity of the emitted electric field. total This represents the scalar value of the total received electric field.

7. The method according to claim 5, characterized in that; Step (3e) generates a small-scale fading simulation point set, simulates the received signal amplitude at each point, and fits the small-scale fading characteristic parameters m and ω. The steps include the following: (3e1) Draw a square with the location of each eavesdropper as the center, and use 10 times the wavelength of the transmitted signal as the side length of the square. Divide the square into N points at equal intervals as simulation points, and write the location information of these points into the second configuration file, N≥5000. (3e2) Repeat steps (3b)-(3d) to obtain the received power and received signal amplitude at each simulation point, and fit the Nakagami-m distribution of the received signal amplitude based on the least squares method, and obtain the shape parameter m and scale parameter ω from the distribution; In step (3c2), the dyadic reflection coefficient at the h-th reflection is calculated. The formula is as follows: in, Let them represent the unit vectors of the incident and reflected rays under parallel polarization in the ray base coordinates, respectively. Let represent the unit vectors of the incident and reflected rays under vertical polarization in the ray base coordinates, respectively. Represents the parallel polarization reflection coefficient. Represents the vertical polarization reflection coefficient. μ represents the intrinsic impedance of the i-th medium. i ε represents the permeability of the i-th medium. i Let represent the dielectric constant of the i-th medium, where i = 1, 2.

8. The method according to claim 6, characterized in that, In step (3c2), the dyadic diffraction coefficient for the j-th diffraction is calculated. The calculation steps include the following: (3c2a) Calculate the parallel polarization reflection coefficient D || : (3c2b) Calculate the vertical polarization reflection coefficient D ⊥ : Where n = θ e / π,θ e Let β0 represent the exterior angle of the diffraction wedge, k represent the wave number, and β0 be the angle between the incident ray and the diffraction edge. Indicates the angle of incidence, Denotes the diffraction angle, F(·), a ± (·) represents two different transition functions, and L represents the distance parameter; (3c2c) Based on the parallel polarization reflection coefficient D || and vertical polarization reflection coefficient D ⊥ Calculate the diffraction coefficient in, Let them represent the unit vectors of the incident ray and the diffracted ray under parallel polarization in the ray base coordinates, respectively. These represent the unit vectors of the incident ray and the diffracted ray under vertical polarization in the ray base coordinates, respectively.

9. The method according to claim 6, characterized in that: In step (3c2), the diffusion factor A of the reflected field is calculated. s1 and the diffusion factor A of the diffracted field s2 The formula is as follows: Where r1 represents the distance from the incident point to the reflection point, and r2 represents the distance from the reflection point to the exit point; s1 represents the distance from the incident point to the diffraction point, and s2 represents the distance from the diffraction point to the exit point; In step (3c3), the radiation field of the transmitted signal at the first node is calculated. and the received electric field originating from the emission source Tx, passing through the i-th ray path, and reaching the receiving point Rx. The formula is as follows: in, The initial value of the emitted electric field is represented by r0, where r0 represents the distance from the emission point to the first ray node, and k represents the wave number. This represents the normalized directivity coefficient of the transmitting antenna. Represents the diatonic reflection coefficient. The dyadic diffraction coefficient, r q This represents the distance from the q-th ray node to the (q+1)-th node. The normalized directivity coefficient of the receiving antenna is represented by n, the total number of reflections is represented by m, and the total number of diffractions is represented by m; A s The diffusion factor is represented by A. When calculating the reflection field, the diffusion factor is determined according to A. s1 Substituting into the calculation, when calculating the diffraction field, the diffusion factor is based on A. s2 Substitute the values ​​into the calculation.

10. The method according to claim 1, characterized in that, Step (4a) Calculate the probability of confidentiality interruption P in a noise-constrained communication scenario. out1 The formula is as follows: Where m represents the shape parameter of the Nakagami-m distribution, ω B ω represents the signal-to-noise ratio of the message signal received by the receiver. E L represents the signal-to-noise ratio of the message signal received by the eavesdropping party. AB L represents the product of the number of transmit antennas and the number of receive antennas. AE R represents the product of the number of transmitting antennas and the number of eavesdropping antennas. th This represents the secrecy breach threshold, and Γ(·) represents the Gamma function. This represents the number of combinations.

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