Non-line-of-sight multipoint physical layer information transmission apparatus

Abstract

The application discloses a non-line-of-sight multipoint physical layer information transmission device, and relates to the technical field of wireless communication.The device comprises a transmitter and an intelligent reflecting surface.The process of transmitting information to a target user comprises the following steps: the transmitter is used for modulating symbol information onto a communication waveform signal by using a modulation technology, and transmitting the communication waveform signal in the form of a beam to the intelligent reflecting surface and the target user; the intelligent reflecting surface is used for reflecting the communication waveform signal transmitted by the transmitter to the target user; and the target user is used for receiving the communication waveform signal transmitted by the transmitter and the communication waveform signal reflected by the intelligent reflecting surface, obtaining a comprehensive communication waveform signal, and extracting symbol information from the comprehensive communication waveform signal by using a demodulation technology.The application can ensure the reliability and safety of information transmission even if there is an obstacle or a long distance between the transmitter and the target user.

Description

Technical Field

[0001] This application relates to the field of wireless communication technology, and in particular to a non-line-of-sight multi-point physical layer information transmission device. Background Technology

[0002] With the widespread adoption of mobile devices and the rise of supercomputer technology, wireless communication technology has developed rapidly, greatly promoting social progress. At the same time, information security issues have become increasingly prominent. Even in wireless communication using advanced encryption technologies, security threats such as confidentiality leaks and network attacks continue to emerge, and the security of wireless communication is facing unprecedented challenges.

[0003] To address this challenge, physical layer security technology has emerged. This technology relies on physical layer methods such as antennas and modulation to achieve secure information transmission, gradually becoming a valuable supplement to traditional encryption mechanisms and building a robust security defense for information transmission. Among these technologies, array antennas not only possess the ability to suppress interference but also effectively enhance desired signals. Furthermore, they exhibit good compatibility with various wireless communication technologies. Utilizing spatial degrees of freedom and antenna gain, they can be effectively applied to physical layer security technology and have become a crucial force driving secure and reliable transmission in modern communications. Therefore, in-depth research into array antenna transmitter technology not only has profound scientific significance but also holds immense application value.

[0004] Currently, most scholars have conducted in-depth research on direct-link communication based on array antennas. However, due to the poor scattering and diffraction capabilities of microwave signals, the attenuation and free path loss of microwave signals during propagation are significant. Therefore, in situations where the transmitter and user are communicating over long distances, or where there are obstacles between the transmitter and user preventing the formation of a direct-link, the information transmission effect of direct-link communication using array antennas is often poor, the reliability of communication is greatly reduced, and normal communication may even fail. Summary of the Invention

[0005] To address one or more of the aforementioned technical problems, this application provides a non-line-of-sight multi-point physical layer information transmission device.

[0006] This application provides a non-line-of-sight multi-point physical layer information transmission device, which adopts the following technical solution: The device includes a transmitter and a smart reflector; the process by which the device sends information to a target user includes: The transmitter is used to modulate symbol information and load it onto a communication waveform signal using modulation technology, and then transmit the communication waveform signal in the form of a beam to the smart reflector and the target user respectively. The intelligent reflective surface is used to reflect the communication waveform signal sent by the transmitter to the target user; The target user is used to receive the communication waveform signal sent by the transmitter and the communication waveform signal reflected by the smart reflector to obtain a comprehensive communication waveform signal, and to extract symbol information from the comprehensive communication waveform signal through demodulation technology.

[0007] By adopting the above technical solution and using an intelligent reflective surface for assistance, combined with a direct link and a link reflected by the intelligent reflective surface, a more reliable communication transmission method and a wider signal coverage are provided through two transmission paths. It can be applied to line-of-sight and non-line-of-sight propagation scenarios between the transmitter and the target user. Even when there are obstructions or long distances between the transmitter and the target user, the reliability and security of information transmission can still be ensured. It effectively solves the problem of poor communication effect of direct transmission links between the transmitter and the target user, or even the security communication problem when there is no direct transmission link due to obstruction. Moreover, the information transmission device of this application is not limited to the case of a single target user. It can realize point-to-multipoint data transmission, which provides the possibility for realizing more complex communication tasks and scenarios.

[0008] In one specific implementation, the transmitter is further configured to add artificial noise to the communication waveform signal, specifically including: The transmitter modulates the symbol information to obtain a modulation symbol vector; The transmitter adds artificial noise to the modulation symbol vector to obtain the transmitted signal vector; The transmitter loads the transmitted signal vector onto the communication waveform signal.

[0009] By adopting the above technical solution, since the eavesdropper passively receives information during the information transmission process, it is impossible to determine whether the eavesdropper's specific location is near the transmitter or near the target user. In order to further avoid information leakage during the information transmission process, artificial noise is also added to the communication waveform.

[0010] In one specific implementation, the modulation symbol vector is: In the formula, Indicates the first Modulation symbols corresponding to each target user satisfy: , , For the set of modulation symbols; The transmitted signal vector is: In the formula, This represents the emitted energy of artificial noise. , Let represent the artificial noise matrix, and , Represents the beamforming matrix. ,and , , Indicates the first modulation symbols The array weighted vector.

[0011] In one specific implementation scheme, the integrated communication waveform signal includes: ; In the formula, Indicates the transmitter to the first A target user's guidance vector. ; Indicates intelligent reflective surface of the first Array steering vector for each target user, ; This represents the reflection coefficient vector of the intelligent reflective surface. , ; Indicating the first intelligent reflective surface Phase-shifted reflection coefficient of each reflecting element, Represents the amplitude reflection coefficient, and ; This represents the guiding matrix of the transmitter to the smart reflector, and ; This represents the transmit signal vector of the transmitter. ; Indicates the first The target user receives additive white Gaussian noise in the channel, and , The variance of the channel's additive white Gaussian noise is given.

[0012] In one specific implementation, the device further includes a parameter optimization controller; the parameter optimization controller is used to optimize the beamforming matrix when the transmitter transmits the beam and the reflection coefficient vector when the smart reflector reflects the signal.

[0013] In one specific implementation, the parameter optimization controller is used to construct a first optimization function with the goal of maximizing the artificial noise transmission power; it is also used to rewrite the first optimization function into a second optimization function based on the total transmission power of the transmitter; and it is also used to solve for the beamforming matrix and the reflection coefficient vector respectively using an alternating iterative algorithm based on the second optimization function. The first optimization function includes: ; In the formula, Represents the target user set; This represents the set of all array weighted vectors; Indicates the first Minimum SINR requirement for each target user; The total transmission power of the transmitter is: In the formula, Indicates modulation symbol The transmission power, and ; The second optimization function includes: ; In one specific implementation scheme, the process by which the parameter optimization controller, based on the second optimization function, solves for the beamforming matrix using an alternating iterative algorithm, specifically includes: Given a reflection coefficient vector ; And define the target user combined channel vector as Then the second optimization function is equivalently transformed into the third optimization function; The third optimization function includes: ; Introducing the autocorrelation matrix ,and And set matrix variables. , , The transformation function is obtained as follows: ; The transformation function is then incorporated into the third optimization function to obtain the fourth optimization function; The fourth optimization function includes: ; The beamforming matrix is ​​obtained by solving the fourth optimization function using a convex optimization tool.

[0014] By adopting the above technical solution, a beamforming matrix is ​​designed with the goal of minimizing transmission power, thereby reducing information leakage and allocating the remaining transmission power to artificial noise. This solves the problem of power allocation between transmitted information and artificial noise, making transmission energy more efficient.

[0015] In one specific implementation scheme, the process by which the parameter optimization controller, based on the second optimization function, solves for the beamforming matrix using an alternating iterative algorithm, specifically includes: Given a beamforming matrix The second optimization function is then equivalently transformed into the fifth optimization function; The fifth optimization function includes: ; make , ,in, The fifth optimization function is then converted into the sixth optimization function. The sixth optimization function includes: ; Introducing auxiliary variables The sixth optimization function is then converted into the seventh optimization function. The seventh optimization function includes: ; In the formula, ; ; Introducing matrix variables And define an intermediate function, where the matrix variable satisfy: , , and Intermediate functions include: ; Based on the intermediate function and the seventh optimization function, the eighth optimization function is obtained; The eighth optimization function includes: ; The reflection coefficient vector is obtained by solving the eighth optimization function using a convex optimization tool.

[0016] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. By employing a reconfigurable intelligent surface (RIS) for assistance, and combining a direct link with a link reflected by the intelligent reflective surface, a more reliable communication transmission method and a wider signal coverage are provided through two transmission paths. It can be applied to line-of-sight and non-line-of-sight propagation scenarios between the transmitter and the target user. Even when there are obstructions or long distances between the transmitter and the target user, the reliability and security of information transmission can still be ensured. This effectively solves the problem of poor communication performance of direct transmission links between the transmitter and the target user, or even the security communication problem when there is no direct transmission link due to obstruction. Moreover, the information transmission device of this application is not limited to the case of a single target user. It can realize point-to-multipoint data transmission, which provides the possibility for realizing more complex communication tasks and scenarios. 2. The beamforming matrix is ​​designed with the goal of minimizing transmission power, thereby reducing information leakage and allocating the remaining transmission power to artificial noise. This solves the problem of power allocation between transmitted information and artificial noise, making transmission energy more efficient. Attached Figure Description

[0017] Figure 1 This is a schematic diagram illustrating the process by which the information transmission device sends information to the target user in an embodiment of this application; Figure 2 This is a curve showing the change in the transmission power of the secure signal as a function of the number of iterations, obtained using an alternating iterative algorithm in the embodiments of this application. Figure 3 This is a curve showing the relationship between the received signal power and the minimum SINR for two target users in this embodiment of the application. Figure 4 This is a curve showing the relationship between the system security capacity and the number of RIS reflective elements for the two target users in this embodiment of the application. Detailed Implementation

[0018] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0019] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0020] In the description of the embodiments of this application, the term "multiple" means two or more. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0021] This application provides a non-line-of-sight multi-point physical layer information transmission device; the device includes: a transmitter and a smart reflector; as shown in the following embodiments: Figure 1 As shown, the process by which the device sends information to the target user is as follows: The transmitter is used to modulate symbol information and load it onto a communication waveform signal using modulation technology, and then transmit the communication waveform signal in the form of a beam to the smart reflector and the target user respectively.

[0022] The intelligent reflective surface is used to reflect the communication waveform signal sent by the transmitter to the target user; The target user is used to receive the communication waveform signal sent by the transmitter and the communication waveform signal reflected by the smart reflector to obtain a comprehensive communication waveform signal, and to extract symbol information from the comprehensive communication waveform signal through demodulation technology.

[0023] Understandably, with such a device, it is impossible for unauthorized users to effectively receive information.

[0024] Therefore, the information transmission device of this application uses a reconfigurable intelligent surface (RIS) for assistance, combining a direct link and a link reflected by the intelligent reflective surface. This provides a more reliable communication transmission method and a wider signal coverage range through two transmission paths. It can be applied to line-of-sight and non-line-of-sight propagation scenarios between the transmitter and the target user. Even when there are obstructions or long distances between the transmitter and the target user, the reliability and security of information transmission can still be ensured. This effectively solves the problem of poor communication effect of direct transmission links between the transmitter and the target user, or even the security communication problem when there is no direct transmission link due to obstruction. Moreover, the information transmission device of this application is not limited to the case of a single target user. It can realize point-to-multipoint data transmission, providing possibilities for realizing more complex communication tasks and scenarios.

[0025] In addition, compared with traditional relay and other active forwarding devices, RIS technology does not require additional power consumption and can reflect the corresponding signal using only low-cost passive devices, thus achieving green communication.

[0026] The information transmission device of this application can be applied to wireless transmission systems, especially information transmission in complex emergency environments, including UAV data links, inter-satellite, satellite-to-ground communication and millimeter wave communication scenarios, to achieve highly secure and reliable wireless data transmission.

[0027] In one possible implementation, to address complex non-line-of-sight communication environments, the configuration of the transmitter and the smart reflector is described in detail below: For the transmitter: The transmitter satisfies both the far-field transmission model and the line-of-sight (LoS) transmission model, and employs a random logarithmic frequency-controlled array antenna. The transmitter comprises... A uniform linear array of antennas, with a spacing of d between each antenna; Considering the target far-field signal transmission model, the first antenna of the transmitter is a reference element, and the frequency increment between antennas is: In the formula, , Indicates the first A unit column vector with each element being 1. , generated randomly and without repetition; This represents the frequency increment of a standard logarithmic frequency control array.

[0028] For intelligent reflective surfaces: The intelligent reflector is a planar array composed of a large number of passive components, where each reflecting unit can independently change the phase shift of the incident electromagnetic wave, thereby giving the electromagnetic wave a specific advantage at the receiving end. Specifically, the intelligent reflector includes components... It consists of several low-cost reflecting units; each reflecting unit can independently change the phase of the incident electromagnetic wave, giving the electromagnetic wave a specific advantage at the receiving end. The intelligent reflector can dynamically adjust the voltage applied to the reflecting units through a controller, causing the reflecting units to exhibit different reflection coefficients, reflecting the incident signal in a specific direction, adjusting the phase and / or amplitude of the received communication waveform signal, and reflecting it to the target user, thus helping to ensure reliable information transmission. It is assumed that the signal power reflected twice or more by the intelligent reflector is negligible.

[0029] In one possible implementation, based on the position information of the smart reflector relative to the transmitter, the position information of the target user relative to the transmitter, and the position information of the target user relative to the smart reflector, corresponding guidance vectors can also be obtained respectively: Specifically, in the far field position The guiding vector is: ; In the formula, ; ; This is the free-space path loss coefficient for wireless signals. c The speed at which electromagnetic waves propagate in a vacuum. For the first The transmission frequency of the antenna.

[0030] In one possible implementation, the transmitter is further configured to add artificial noise to the communication waveform signal, specifically including the following steps A1-A3: A1, the transmitter modulates the symbol information to obtain a modulation symbol vector; It is understandable that modulation is the process of converting a stream of information bits into a signal form suitable for transmission through a channel. In this process, information bits are mapped onto specific modulation symbols, thus forming a modulation symbol vector.

[0031] The modulation symbol vector is: In the formula, Indicates the first Modulation symbols corresponding to each target user satisfy: , , For the set of modulation symbols; A2, the transmitted signal vector is: In the formula, This represents the emitted energy of artificial noise. , where z is a random vector following a complex Gaussian distribution, used to generate random artificial noise signals; Let represent the artificial noise matrix, and ; Represents the beamforming matrix. ,and , , Indicates the first modulation symbols The array weighted vector.

[0032] As will be understood by those skilled in the art, initially, the transmitted signal vector is represented as: Specifically, it is expressed as .

[0033] A3, the transmitter loads the transmitted signal vector onto the communication waveform signal.

[0034] Since the eavesdropper passively receives information during the transmission process and cannot determine whether the eavesdropper is near the transmitter or near the target user, artificial noise is added to the communication waveform to further prevent information leakage.

[0035] In one possible implementation, the transmitter is also used to pre-construct an artificial noise matrix and generate artificial noise based on the artificial noise matrix.

[0036] Specifically, the artificial noise matrix is: ; In the formula, .

[0037] The process of constructing the artificial noise matrix is ​​explained below: First, an initial artificial noise matrix is ​​constructed, ensuring that the artificial noise interferes with the eavesdropper without affecting the target user's signal reception. The initial artificial noise matrix includes: ; In the formula, , tr is the rank operation for a matrix; Then, assuming The initial artificial noise matrix can then be simplified to: ; Finally, based on the null space mapping criterion, the artificial noise matrix can be constructed as follows: , .

[0038] In one possible implementation, the resulting integrated communication waveform signal for the target user is further described below: Due to the introduction of the intelligent reflector, the target user can receive both the direct signal transmitted from the transmitter and the reflected signal from the intelligent reflector. The received combined communication waveform signal is as follows: ; In the formula, Indicates the transmitter to the first A target user's guidance vector. ; Indicates intelligent reflective surface of the first Array steering vector for each target user, ; This represents the reflection coefficient vector of the intelligent reflective surface. , , It is an M-dimensional diagonal matrix; Indicating the first intelligent reflective surface Phase-shifted reflection coefficient of each reflecting element, Represents the amplitude reflection coefficient, and ; This represents the guiding matrix of the transmitter to the smart reflector, and ; This represents the transmit signal vector of the transmitter. ; Indicates the first The target user receives additive white Gaussian noise in the channel, and , The variance of the channel additive white Gaussian noise will be used for simplicity in the following text. Recorded as .

[0039] Furthermore, combining the above expression for the transmitted signal vector s, that is... We can obtain: ; In one possible implementation, the device further includes a parameter optimization controller; the parameter optimization controller is used to optimize the beamforming matrix when the transmitter transmits a beam and the reflection coefficient vector when the smart reflector reflects a signal.

[0040] Furthermore, the process of optimizing the beamforming matrix when the transmitter transmits the beam and the reflection coefficient vector when the smart reflector reflects the signal specifically includes the following steps B1-B3: B1. Considering a scenario where the eavesdropper is completely concealed, and assuming the total transmit power of the transmitter is fixed, the artificial noise transmit power is maximized to increase interference with the eavesdropper, while ensuring the target user meets the minimum receive power constraint. According to the design criteria, the parameter optimization controller first constructs a first optimization function based on the optimization problem, with the objective of maximizing the artificial noise transmit power. The first optimization function includes: ; In the formula, Represents the target user set; This represents the set of all array weighted vectors; Indicates the first Minimum SINR requirement for each target user; Let represent the complex reflection coefficient of the m-th reflecting element, then .

[0041] B2, the parameter optimization controller rewrites the first optimization function into a second optimization function based on the total transmit power of the transmitter; The total transmission power of the transmitter is: In the formula, Indicates modulation symbol The transmission power, and ; Based on the function of the total transmitter power, it is easy to see that the artificial noise transmission power can be maximized by minimizing the modulation symbol transmission power; therefore, the second optimization function includes: .

[0042] B3, the parameter optimization controller, based on the second optimization function, uses an alternating iterative algorithm to solve for the beamforming matrix and the reflection coefficient vector.

[0043] Specifically, step B3 includes the following steps B301-B310: B301, given reflection coefficient vector ; And define the target user combined channel vector as Then the second optimization function is equivalently transformed into the third optimization function; The third optimization function includes: .

[0044] B302, to obtain the optimal solution, an autocorrelation matrix is ​​introduced. , represented as ; And set matrix variables , , ; Then the transformation function can be obtained: .

[0045] B303, the transformation function is introduced into the third optimization function to obtain the fourth optimization function; The fourth optimization function includes: ; B304, where the fourth optimization function is a convex optimization problem, conventional convex optimization tools can be used to obtain the optimal solution corresponding to the fourth optimization function, thereby obtaining the beamforming matrix. Furthermore, if the optimal matrix corresponding to the fourth optimization function is obtained... If the rank is greater than 1, then randomization and scaling operations can be used to obtain an approximate vector solution.

[0046] B305, Given beamforming matrix The second optimization function is then equivalently transformed into the fifth optimization function; The fifth optimization function includes: ; At this point, the function has been transformed into solving for the reflection coefficient vector that satisfies the constraints. .

[0047] B306, to make the optimization problem easier to handle, here we set... , ,in, Then the fifth optimization function is converted into the sixth optimization function; The sixth optimization function includes: ; It can be seen that the optimization problem corresponding to the sixth optimization function is still non-convex, and the optimal solution cannot be obtained through traditional convex optimization. Therefore, other variables are introduced for transformation.

[0048] B307, Introducing Auxiliary Variables The sixth optimization function is then converted into the seventh optimization function. The seventh optimization function includes: ; In the formula, ; ; B308, the optimization problem is solved using SDR, therefore matrix variables are introduced. And define an intermediate function, where the matrix variable satisfy: , , and Intermediate functions include: .

[0049] B309, based on the intermediate function and the seventh optimization function, the eighth optimization function is obtained; The eighth optimization function includes: ; B310, At this point, solving the eighth optimization function has been transformed into a convex optimization problem. Conventional convex optimization tools can now be used to solve the eighth optimization function, thereby obtaining the reflection coefficient vector. Similarly, if the optimal matrix is ​​obtained... If the rank is greater than 1, then randomization and scaling operations can be used to obtain an approximate vector solution.

[0050] Those skilled in the art will understand that conventional convex optimization tools, such as those in MATLAB, can be used.

[0051] At this point, the beamforming matrix and the reflection coefficient vector have been solved.

[0052] Therefore, by designing the beamforming matrix with the goal of minimizing transmission power, information leakage is reduced, and the remaining transmission power is allocated to artificial noise. This solves the problem of power allocation between the existing transmitted information and artificial noise, making the transmission energy more efficient.

[0053] Furthermore, for ease of understanding, the above alternating iterative algorithm is summarized in Table 1: Table 1. Main steps of the alternating iterative optimization algorithm Step 1 <![CDATA[Initialize the number of iterations r=1, and randomly generate the reflection coefficient vector φ r .]]> Step Two <![CDATA[According to the above steps, when the reflection coefficient vector φ is given r , the corresponding beamforming matrix W is solved r .]]> Step 3 <![CDATA[According to the above steps, when the beamforming matrix W is given r , the corresponding reflection coefficient vector φ is solved r+1 .]]> Step Four The number of update iterations is r = r + 1. Step 5 Determine if the loop termination condition is met; if not, return to step two. Furthermore, since iterative algorithms may cause the problem to diverge, the convergence of the alternating iterative algorithm used in this application is proven below.

[0054] definition If the optimal objective value is to be obtained in the i-th iteration, then we have .definition As the number of iterations increases, The value gradually approaches 0, and the algorithm converges.

[0055] Proof process: According to the alternating iteration algorithm, it can be known that To pass the first The feasible solution obtained in step two of the next iteration. To pass the first The feasible solution obtained in step two of the next iteration. Similarly, according to the alternating iteration algorithm, we can obtain... For the first A feasible solution in step three of the next iteration. For a given reflection coefficient vector In step two, the function is solved to obtain the optimal solution, which is the beamforming matrix. Therefore, we can conclude that: ; It is easy to see that the objective function in the proposed optimization problem is only related to the beamforming matrix. Therefore, we can conclude that: ; Based on the two formulas above, we can derive:

[0056] In summary, the objective value generated by the alternating iterative algorithm of this application is a non-increasing sequence. At the same time, due to the constraint of the target user receiving SINR, the objective function in the above optimization problem is bounded. Therefore, the alternating iterative algorithm involved can guarantee convergence to a local optimum.

[0057] The advantages of this application's solution will be explained in detail below, based on simulation results: In the simulation, the specific deployment of the device is as follows: the transmitter consists of a uniform linear array located along the x-axis, and its reference antenna is positioned as follows: The intelligent reflective surface consists of a uniform planar array located in the xy-plane, with its reference reflective element positioned as follows: The target user is located in the xy plane, and their position is... The transmission distance between the transmitter and the target user is... The transmission distance between the intelligent reflective surface and the target user is .

[0058] Assume there are two target users, and multiple passive eavesdroppers. Target user 1's location is... The location of target user 2 is There is an obstruction between the transmitter and target user 2. The target user's minimum received SINR is equal, i.e. The channel noise is equal, that is... .

[0059] like Figure 2 The figure shows the curve of the secure signal transmission power changing with the number of iterations obtained using the alternating iterative algorithm. As can be seen from the figure, the alternating iterative algorithm converges quickly, requiring only 10 iterations to obtain the minimum secure signal transmission power and achieve convergence.

[0060] like Figure 3 As shown, the total received modulation symbol power of the two target users is represented respectively. Transmitter direct transmission modulation symbol power RIS reflection modulation symbol power and interference signal power The relationship between the target user's minimum received SINR and the signal reception frequency (SINR) is shown in the figure. As can be seen, target user 1, being closer to the transmitter, primarily relies on the transmitter's direct transmission link to receive signals. Target user 2, however, due to obstructions in the transmitter's direct transmission link, primarily relies on the intelligent reflector's reflection link to receive signals. Simultaneously, by optimizing the beamforming matrix, reflection coefficient matrix, and artificial noise matrix, the minimum received SINR requirements for both target user 1 and target user 2 are ensured.

[0061] like Figure 4As shown, the relationship between the system security capacity and the intelligent reflective surface reflective elements for two target users is illustrated. For target user 1, the system security capacity corresponding to the proposed solution is equal to that of the traditional frequency control array solution, both ensuring secure information transmission. For target user 2, the proposed solution is significantly superior to the traditional frequency control array solution. As the number of intelligent reflective surface reflective elements increases, the security capacity of the proposed solution also increases, while the security capacity based on the traditional frequency control array remains at a low level. When there is an obstruction in the direct transmission link between the transmitter and target user 2, the traditional frequency control array secure communication solution cannot guarantee reliable information reception for target user 2, allowing eavesdroppers to steal confidential information by continuously approaching the transmitter.

[0062] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A non-line-of-sight multi-point physical layer information transmission device, characterized in that, Includes the transmitter and the smart reflector; The process by which the information transmission device sends information to the target user includes: The transmitter is used to modulate symbol information and load it onto a communication waveform signal using modulation technology, and then transmit the communication waveform signal in the form of a beam to the smart reflector and the target user respectively. The transmitter is further configured to add artificial noise to the communication waveform signal, specifically including: the transmitter modulating symbol information to obtain a modulation symbol vector; the transmitter adding artificial noise to the modulation symbol vector to obtain a transmission signal vector; and the transmitter loading the transmission signal vector onto the communication waveform signal. The intelligent reflective surface is used to reflect the communication waveform signal sent by the transmitter to the target user; The target user is used to receive the communication waveform signal sent by the transmitter and the communication waveform signal reflected by the smart reflector to obtain a comprehensive communication waveform signal, and extract symbol information from the comprehensive communication waveform signal through demodulation technology; The information transmission device further includes a parameter optimization controller, which is used to optimize the beamforming matrix when the transmitter transmits the beam and the reflection coefficient vector when the intelligent reflector reflects the signal. Specifically, the parameter optimization controller is used to construct a first optimization function with the goal of maximizing the artificial noise transmission power; it is also used to rewrite the first optimization function into a second optimization function based on the total transmission power of the transmitter; and it is also used to solve for the beamforming matrix and the reflection coefficient vector respectively based on the second optimization function using an alternating iterative algorithm.

2. The non-line-of-sight multi-point physical layer information transmission device according to claim 1, characterized in that, The modulation symbol vector is: In the formula, Indicates the first Modulation symbols corresponding to each target user satisfy: , , For the set of modulation symbols, Indicates the total number of target users; The transmitted signal vector is: In the formula, This represents the emitted energy of artificial noise. , Let represent the artificial noise matrix, and , Indicates the number of antennas on the transmitter. Represents the beamforming matrix. ,and , , Indicates the first modulation symbols The array weighted vector.

3. The non-line-of-sight multi-point physical layer information transmission device according to claim 1, characterized in that, The integrated communication waveform signal includes: ； In the formula, Indicates the transmitter to the first A target user's guidance vector. ; Indicates intelligent reflective surface of the first Array steering vector for each target user, , This indicates the total number of reflective units on the intelligent reflective surface; This represents the reflection coefficient vector of the intelligent reflective surface. , ; Indicating the first intelligent reflective surface Phase-shifted reflection coefficient of each reflecting element, Represents the amplitude reflection coefficient, and ; This represents the guiding matrix of the transmitter to the smart reflector, and ; This represents the transmit signal vector of the transmitter. ; Indicates the first The target user receives additive white Gaussian noise in the channel, and , The variance of the channel's additive white Gaussian noise is given.

4. The non-line-of-sight multi-point physical layer information transmission device according to claim 1, characterized in that: The first optimization function includes, ； In the formula, Represents the target user set; This represents the set of all array weighted vectors; Indicates the first Minimum SINR requirement for each target user; The total transmission power of the transmitter is [value missing]. In the formula, Indicates modulation symbol The transmission power, and ; The second optimization function includes, 。 5. The non-line-of-sight multi-point physical layer information transmission device according to claim 1, characterized in that, The parameter optimization controller, based on the second optimization function, employs an alternating iterative algorithm to solve for the beamforming matrix. The process specifically includes: Given a reflection coefficient vector ; And define the target user combined channel vector as Then the second optimization function is equivalently transformed into the third optimization function; The third optimization function includes: ； Introducing the autocorrelation matrix ,and And set matrix variables. , , The transformation function is obtained as follows: ; The transformation function is then incorporated into the third optimization function to obtain the fourth optimization function; The fourth optimization function includes: ； The beamforming matrix is ​​obtained by solving the fourth optimization function using a convex optimization tool.

6. The non-line-of-sight multi-point physical layer information transmission device according to claim 1, characterized in that, The parameter optimization controller, based on the second optimization function, employs an alternating iterative algorithm to solve for the beamforming matrix. The process specifically includes: Given a beamforming matrix The second optimization function is then equivalently transformed into the fifth optimization function; The fifth optimization function includes: ； make , ,in, The fifth optimization function is then converted into the sixth optimization function. The sixth optimization function includes: ； Introducing auxiliary variables The sixth optimization function is then converted into the seventh optimization function. The seventh optimization function includes: ； In the formula, ; ; Introducing matrix variables And define an intermediate function, where the matrix variable satisfy: , , and Intermediate functions include: ; Based on the intermediate function and the seventh optimization function, the eighth optimization function is obtained; The eighth optimization function includes: ； The reflection coefficient vector is obtained by solving the eighth optimization function using a convex optimization tool.

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