Non-line-of-sight multi-point physical layer information transmission device

Abstract

The invention discloses a non-line-of-sight multi-point physical layer information transmission device, and relates to the technical field of wireless communication, and the device comprises a transmitter and an intelligent reflection surface. The process of sending information to the target user by the device comprises the following steps: the transmitter is used for modulating code element information by adopting a modulation technology, loading the code element information to a communication waveform signal, and respectively transmitting the communication waveform signal to the intelligent reflecting surface and the target user in a beam form; the intelligent reflecting surface is used for reflecting the communication waveform signal sent by the transmitter to the target user; and the target user is used for receiving the communication waveform signal sent by the transmitter and the communication waveform signal reflected by the intelligent reflecting surface to obtain a comprehensive communication waveform signal, and extracting code element information from the comprehensive communication waveform signal through a demodulation technology. According to the invention, under the condition that the transmitter and the target user are blocked or the distance between the transmitter and the target user is long, the reliability and safety of information transmission can still be ensured.

Description

Technical Field

[0001] The present 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 Art

[0002] With the popularization 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 communications that use advanced encryption technology, security threats such as confidentiality leaks and network attacks continue to emerge. The security of wireless communications is facing unprecedented challenges.

[0003] In order to meet this challenge, physical layer security technology came into being. This technology relies on physical layer means such as antennas and modulation to achieve secure information transmission, and has gradually become a beneficial supplement to traditional encryption mechanisms, building a solid security line for information transmission. Among them, array antennas not only have the ability to suppress interference, but also can effectively enhance the desired signal. At the same time, they have good compatibility with a variety of wireless communication technologies. They use spatial degrees of freedom and antenna gain, and can be effectively applied to physical layer security technology. It has become an important force in promoting modern communications to achieve secure and reliable transmission. Therefore, in-depth research on array antenna transmitter technology not only has far-reaching scientific significance, but also contains huge application value.

[0004] At present, 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 frequency band signals, the attenuation and spatial free path loss of microwave frequency band signals during propagation are large. Therefore, when the transmitter and the user communicate over a long distance, or there is an obstruction between the transmitter and the user and a direct link cannot be formed, the effect of information transmission using the direct link of the array antenna is often poor, the reliability of communication is greatly reduced, and even normal communication cannot be achieved. Summary of the invention

[0005] In order to solve one or more of the above technical problems, the present application provides a non-line-of-sight multi-point physical layer information transmission device.

[0006] The present 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 an intelligent reflective surface; the process of the device sending information to a target user includes: The transmitter is used to adopt a modulation technology to modulate the code element information and load it onto the communication waveform signal, and transmit the communication waveform signal in the form of a beam to the smart reflection surface and the target user respectively; The intelligent reflection 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 reflection surface, obtain a comprehensive communication waveform signal, and extract code element information from the comprehensive communication waveform signal through demodulation technology.

[0007] By adopting the above technical solution, using an intelligent reflecting surface for assistance, combining a direct link and a link reflected by an intelligent reflecting surface, a more reliable communication transmission method and a wider signal coverage range are provided through two transmission paths, and can be applied to line-of-sight propagation scenarios and non-line-of-sight propagation scenarios between a transmitter and a target user. When there is an obstruction or a long distance between the transmitter and the target user, the reliability and security of information transmission can still be ensured, which well solves the problem of poor communication effect of the direct link between the transmitter and the target user, or even the problem of secure communication when the direct link does not exist due to obstruction; moreover, the information transmission device of the present application is not limited to the case where the target user is a single, and point-to-multipoint transmission of data can be realized, which provides the possibility of realizing more complex communication tasks and scenarios.

[0008] In a specific implementation scheme, the transmitter is further used to add artificial noise to the communication waveform signal, specifically comprising: The transmitter modulates the code element information to obtain a modulation symbol vector; The transmitter adds artificial noise on the basis of the modulation symbol vector to obtain a transmission signal vector; The transmitter loads the transmission 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 a specific implementation scheme, the modulation symbol vector is: x=[x1, x2, ..., x v ,…,x V ] T ; In the formula, x v represents the modulation symbol corresponding to the vth target user, x v Satisfies: E(|x v | 2 )=1,x v ∈Φ, Φ is the modulation symbol set; The transmit signal vector is: Where P AN represents the emission energy of artificial noise, T AN represents the artificial noise matrix, and T AN ∈C N×N ;W represents the beamforming matrix, W∈C N×V , and W=[w1,w2,…,w v ,…,w V ] T , w v =[w v,1 ,w v,2 ,…,w v,n ,…,w v,N ] T , w v represents the vth modulation symbol x v An array of weight vectors.

[0011] In a specific implementation scheme, the integrated communication waveform signal includes: In the formula, h AL,v represents the guidance vector of the transmitter to the vth target user, h AL,v ∈C N×1 ; h RL, v represents the array steering vector of the vth target user facing the intelligent reflection, h RL,v ∈C M×1 ; Φ represents the reflection coefficient vector of the smart reflective surface, Φ∈C M×M ; θ m represents the phase shift reflection coefficient of the mth reflection element in the smart reflection surface, α represents the amplitude reflection coefficient, and α∈(0,1]; H1 represents the guidance matrix of the transmitter to the smart reflection surface, and H1∈C N×M ; s represents the transmitted signal vector of the transmitter, n L,v represents the channel additive white Gaussian noise received by the vth target user, and is the channel additive white Gaussian noise variance.

[0012] In a specific implementation scheme, the device also 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 reflection surface reflects a signal.

[0013] In a specific feasible implementation scheme, the parameter optimization controller is used to construct a first optimization function with the goal of maximizing the artificial noise transmission power; is also used to rewrite the first optimization function into a second optimization function based on the total transmission power of the transmitter; is also used to respectively solve the beamforming matrix and the reflection coefficient vector based on the second optimization function by using an alternating iterative algorithm; Wherein, the first optimization function comprises: In the formula, V represents the target user set; represents the set of all array weight vectors; γ v represents the minimum SINR requirement of the vth target user; The total transmission power of the transmitter is: Where P L,v Represents the modulation symbol x v The transmission power of The second optimization function comprises:

[0014] In a specific implementation scheme, the parameter optimization controller uses an alternating iterative algorithm based on the second optimization function to solve the beamforming matrix, which specifically includes: Given a reflection coefficient vector And define the target user combined channel vector as Then the second optimization function is equivalently converted into a third optimization function; Wherein, the third optimization function includes: Introduce the autocorrelation matrix X v ∈C N×N ,and And set the matrix variable W v ≥0, rank(W v )=1, Get the transformation function: Introducing the transformation function into the third optimization function to obtain a fourth optimization function; Wherein, the fourth optimization function includes: The fourth optimization function is solved by using a convex optimization tool to obtain the beamforming matrix.

[0015] By adopting the above technical solution, the beamforming matrix is ​​designed with the minimum transmission power as the goal, thereby reducing information leakage and allocating the remaining transmission power to artificial noise, solving the existing power allocation problem of transmitting information power and artificial noise power, making the transmission energy more efficient.

[0016] In a specific implementation scheme, the parameter optimization controller uses an alternating iterative algorithm based on the second optimization function to solve the beamforming matrix, which specifically includes: Given a beamforming matrix W, the second optimization function is equivalently converted into a fifth optimization function; Wherein, the fifth optimization function includes: make i=1,2,…,V, i=1,2,…,V,where, Converting the fifth optimization function into a sixth optimization function; Wherein, the sixth optimization function includes: Introducing an auxiliary variable μ to convert the sixth optimization function into a seventh optimization function; Wherein, the seventh optimization function includes: In the formula, Introduce a matrix variable A and define an intermediate function, where the matrix variable A satisfies: A∈C (M+1)×(M+1) , A≥0, and rank(A)=1; intermediate functions include: Based on the intermediate function and the seventh optimization function, an eighth optimization function is obtained; Wherein, the eighth optimization function includes: Find A The eighth optimization function is solved using a convex optimization tool to obtain the reflection coefficient vector.

[0017] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Using a reconfigurable intelligent surface (RIS) for assistance, combining a direct link and a link reflected by a smart reflective surface, a more reliable communication transmission mode and a wider signal coverage range are provided through two transmission paths, which can be applied to line-of-sight and non-line-of-sight transmission scenarios between the transmitter and the target user. When there is an obstruction or a long distance between the transmitter and the target user, the reliability and security of information transmission can still be ensured, which well solves the problem of poor communication effect of the direct link between the transmitter and the target user, or even the problem of secure communication when there is no direct link due to obstruction; moreover, the information transmission device of the present application is not limited to the case where the target user is a single one, and point-to-multipoint transmission of data can be realized, which makes it possible to realize more complex communication tasks and scenarios; 2. Design the beamforming matrix with the minimum transmit power as the goal, thereby reducing information leakage and allocating the remaining transmit power to artificial noise, solving the power allocation problem of existing transmitted information and artificial noise, making the transmit energy more efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a schematic diagram of a process in which an information transmission device sends information to a target user in an embodiment of the present application; Figure 2 is a curve of the change of the confidentiality signal transmission power with the number of iterations obtained by using the alternating iterative algorithm in the embodiment of the present application; Figure 3 is a relationship curve between the received signal power and the minimum SINR corresponding to the two target users in the embodiment of the present application; Figure 4 It is a relationship curve between the system safety capacity corresponding to the two target users and the number of RIS reflective elements in the embodiment of the present application. DETAILED DESCRIPTION

[0019] In order to enable technicians in this field 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 in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0020] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0021] In the description of the embodiments of the present application, the term "plurality" means two or more. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0022] The present application embodiment provides a non-line-of-sight multi-point physical layer information transmission device; the device includes: a transmitter and a smart reflective surface; Figure 1 As shown, the process of the device sending information to the target user is as follows: The transmitter is used to adopt modulation technology to modulate the code element information and load it onto the communication waveform signal, and transmit the communication waveform signal in the form of beams to the smart reflection surface and the target user respectively.

[0023] The intelligent reflection 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 reflection surface, obtain a comprehensive communication waveform signal, and extract code element information from the comprehensive communication waveform signal through demodulation technology.

[0024] It is understandable that, through such a device, non-legal users will not be able to effectively receive information.

[0025] Therefore, the information transmission device of the present application is assisted by a Reconfigurable Intelligent Surface (RIS), and combines a direct link and a link reflected by the intelligent reflecting surface to provide a more reliable communication transmission mode and a wider signal coverage range through two transmission paths. It can be applied to line-of-sight and non-line-of-sight transmission scenarios between the transmitter and the target user. When there is an obstruction or the distance is long between the transmitter and the target user, the reliability and security of information transmission can still be ensured, which well solves the problem of poor communication effect of the direct link between the transmitter and the target user, or even the problem of secure communication when the direct link does not exist due to obstruction. Moreover, the information transmission device of the present application is not limited to the case where the target user is a single one, and point-to-multipoint transmission of data can be realized, which provides the possibility of realizing more complex communication tasks and scenarios.

[0026] In addition, compared with active forwarding devices such as traditional relays, RIS technology does not require additional power consumption and only relies on low-cost passive devices to reflect the corresponding signals, achieving green communication.

[0027] The information transmission device of the present application can be applied to wireless transmission systems, especially information transmission in complex emergency environments, including drone data links, inter-satellite, satellite-to-ground communications, and millimeter wave communication scenarios, to achieve highly confidential and reliable wireless transmission of data.

[0028] In a possible implementation manner, in order to cope with a non-line-of-sight complex communication environment, the composition of the transmitter and the smart reflective surface is specifically described below: For the transmitter: The transmitter satisfies a far-field transmission model and a line of sight (LoS) transmission model, and adopts a random logarithmic frequency-controlled array antenna. The transmitter includes a uniform linear array composed of N antennas, and the spacing between each antenna is d; Considering the target far-field signal transmission model, the first antenna of the transmitter is the reference array element, and the frequency increment between antennas is: Δf LR =P T Δf; where P = [c1, c2, ..., c i ,…,c N ], c i represents the unit column vector whose i-th element is 1, i∈{1,2,…,N}, which is randomly generated and non-repeating; Δf represents the frequency increment of the standard logarithmic frequency-controlled array.

[0029] For smart reflective surfaces: The smart reflective surface is a planar array composed of a large number of passive devices, each of which can independently change the phase shift of the incident electromagnetic wave, so that the electromagnetic wave has a specific advantage at the receiving end. Specifically, the smart reflective surface is composed of M low-cost reflective units; each reflective unit can independently change the phase of the incident electromagnetic wave, so that the electromagnetic wave has a specific advantage at the receiving end. The smart reflective surface can dynamically adjust the voltage applied to the reflective unit through a controller, so that the reflective unit presents a different reflection coefficient, reflects its incident signal in a specific direction, adjusts the phase and / or amplitude of the received communication waveform signal, and reflects it to the target user, helping to transmit information reliably. It is assumed that the signal power reflected twice or more by the smart reflective surface can be ignored.

[0030] In a possible implementation manner, corresponding steering vectors may be obtained respectively according to the position information of the smart reflective surface 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 reflective surface: Specifically, the steering vector at the far-field position (r,θ) is: h(f,r,θ,t)=ρ[h1(f1,r,θ,t),…,h n (fn ,r,θ,t),…,h N (f N ,r,θ,t)] T In the formula, n=1,2,…,N; ρ is the free space path loss coefficient of the wireless signal, c is the propagation speed of electromagnetic waves in a vacuum, f n is the transmitting frequency of the nth antenna.

[0031] In a possible implementation manner, the transmitter is further used to add artificial noise to the communication waveform signal, specifically including the following steps A1-A3: A1, the transmitter modulates the code element information to obtain a modulation symbol vector; It can be understood that modulation is the process of converting an information bit stream into a signal form suitable for channel transmission. In this process, the information bits are mapped to specific modulation symbols to form a modulation symbol vector.

[0032] Among them, the modulation symbol vector is: x=[x1,x2,…,x v ,…,x V ] T ; In the formula, x v represents the modulation symbol corresponding to the vth target user, x v Satisfies: E(|x v | 2 )=1,x v ∈Φ, Φ is the modulation symbol set; A2, the transmitter adds artificial noise on the basis of the modulation symbol vector to obtain a transmission signal vector; Wherein, the transmission signal vector is: Where P AN represents the emission energy of artificial noise, T AN represents the artificial noise matrix, and T AN ∈C N×N ;W represents the beamforming matrix, W∈C N×V , and W=[w1,w2,…,w v ,…,w V ] T , w v =[w v,1 ,w v,2 ,…,w v,n ,…,w v,N ] T , w v represents the vth modulation symbol x v An array of weight vectors.

[0033] It can be understood by those skilled in the art that, initially, the transmitted signal vector is represented as: s = [s1, s2, ..., s n ,…,s N ], specifically expressed as

[0034] A3, the transmitter loads the transmission signal vector onto the communication waveform signal.

[0035] 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.

[0036] In a possible implementation manner, the transmitter is further configured to pre-construct an artificial noise matrix and generate artificial noise based on the artificial noise matrix.

[0037] Specifically, the artificial noise matrix is: In the formula, H3=[H AL ,H ARL ].

[0038] The following explains the process of constructing the artificial noise matrix: Firstly, the initial artificial noise matrix is ​​constructed under the premise of ensuring that the artificial noise interferes with the eavesdropper while not affecting the target user's receiving signal; Among them, the initial artificial noise matrix includes: In the formula, tr is the matrix rank operation; Afterwards, assuming Then the initial artificial noise matrix can be simplified as: Finally, according to the null space mapping criterion, the artificial noise matrix can be constructed as: H3=[H AL ,H ARL ].

[0039] In a possible implementation manner, the integrated communication waveform signal obtained by the target user is further described below: Due to the introduction of the intelligent reflective surface, the target user can receive the direct signal from the transmitter and the reflected signal from the intelligent reflective surface. The received comprehensive communication waveform signal is: In the formula, h AL,v represents the guidance vector of the transmitter to the vth target user, h AL,v ∈C N×1; h RL,v represents the array steering vector of the vth target user facing the intelligent reflection, h RL,v ∈C M×1 ; Φ represents the reflection coefficient vector of the smart reflective surface, Φ∈C M×M , Φ is an M-dimensional diagonal matrix; θ m represents the phase shift reflection coefficient of the mth reflection element in the smart reflection surface, α represents the amplitude reflection coefficient, and α∈(0,1]; H1 represents the guiding matrix of the transmitter to the smart reflector, and H1∈C N×M ; s represents the transmitted signal vector of the transmitter, n L,v represents the channel additive white Gaussian noise received by the vth target user, and is the channel additive white Gaussian noise variance.

[0040] Furthermore, combined with the above expression of the transmitted signal vector s, that is, You can get: In a possible implementation, the device further includes a parameter optimization controller; the parameter optimization controller is used to optimize a beamforming matrix when the transmitter transmits a beam and a reflection coefficient vector when the smart reflection surface reflects a signal.

[0041] Furthermore, the process of optimizing the beamforming matrix when the transmitter transmits a beam and the reflection coefficient vector when the smart reflector reflects a signal specifically includes the following steps B1-B3: B1, considering the scenario where the eavesdropper is completely hidden, assuming that the total transmission power of the transmitter is fixed, and under the constraint that the target user meets the minimum receiving power, maximize the artificial noise transmission power to increase the interference to the eavesdropper. According to the design criteria, the parameter optimization controller first constructs a first optimization function based on the optimization problem with the goal of maximizing the artificial noise transmission power; wherein the first optimization function includes: In the formula, V represents the target user set; represents the set of all array weight vectors; γ v represents the minimum SINR requirement of the vth target user; The constraint condition states that all target users need to meet the minimum SINR requirement.

[0042] B2, the parameter optimization controller rewrites the first optimization function into a second optimization function based on the total transmit power of the transmitter; Wherein, the total transmission power of the transmitter is: Where P L,v Represents the modulation symbol x v The transmission power of According to the function of the total transmission power of the transmitter, it is easy to find that the artificial noise transmission power can be maximized by minimizing the modulation symbol transmission power; therefore, the second optimization function includes:

[0043] B3, the parameter optimization controller, based on the second optimization function, uses an alternating iterative algorithm to solve the beamforming matrix and the reflection coefficient vector.

[0044] Specifically, step B3 includes the following steps B301-B310: B301, given the reflection coefficient vector And define the target user combined channel vector as Then the second optimization function is equivalently converted into a third optimization function; Wherein, the third optimization function includes:

[0045] B302, to obtain the optimal solution, introduce the autocorrelation matrix X v ∈C N×N , expressed as And set the matrix variable W v ≥0, rank(W v )=1, Then we can get the transformation function:

[0046] B303, introducing the transformation function into the third optimization function to obtain a fourth optimization function; Wherein, the fourth optimization function includes: B304, the fourth optimization function is a convex optimization problem. At this time, conventional convex optimization tools can be used to obtain the optimal solution corresponding to the fourth optimization function, thereby obtaining the beamforming matrix. Further, if the optimal matrix corresponding to the fourth optimization function is obtained If the rank of is greater than 1, randomization and scaling operations can be used to obtain an approximate vector solution.

[0047] B305, given a beamforming matrix W, and converting the second optimization function into a fifth optimization function equivalently; Wherein, the fifth optimization function includes: At this point, the function has been transformed into solving the reflection coefficient vector that satisfies the constraints

[0048] B306, in order to make the optimization problem easier to handle, i=1,2,…,V, i=1,2,…,V,where, Then the fifth optimization function is converted into a sixth optimization function; Wherein, the sixth optimization function includes:

[0049] It can be obtained 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.

[0050] B307, introducing an auxiliary variable μ to convert the sixth optimization function into a seventh optimization function; Wherein, the seventh optimization function includes: In the formula,

[0051] B308, solve the optimization problem according to SDR, so introduce the matrix variable A and define the intermediate function, where the matrix variable A satisfies: A∈C (M+1)×(M+1) , A≥0, and rank(A)=1; intermediate functions include:

[0052] B309, obtaining an eighth optimization function based on the intermediate function and the seventh optimization function; Wherein, the eighth optimization function includes: Find A.

[0053] B310, so far, the solution of the eighth optimization function has been converted into a convex optimization problem. At this time, the eighth optimization function can be solved by using conventional convex optimization tools to obtain the reflection coefficient vector; similarly, if the optimal matrix A is obtained * If the rank of is greater than 1, randomization and scaling operations can be used to obtain an approximate vector solution.

[0054] Those skilled in the art will appreciate that conventional convex optimization tools, such as convex optimization tools in MATLAB, may be used.

[0055] So far, the beamforming matrix and the reflection coefficient vector have been solved.

[0056] Therefore, the beamforming matrix is ​​designed with the minimum transmit power as the goal, thereby reducing information leakage and allocating the remaining transmit power to artificial noise, solving the power allocation problem of existing transmitted information and artificial noise, making the transmit energy more efficient.

[0057] Further, for ease of understanding, the above alternating iterative algorithm is summarized as Table 1 below: Table 1 Main steps of the alternating iterative optimization algorithm Furthermore, since the iterative algorithm may cause the problem to diverge, the convergence of the alternating iterative algorithm used in this application is demonstrated below.

[0058] definition is the optimal target value of the rth iteration, then definition As the number of iterations increases, the value of |Δl| gradually approaches 0, and the algorithm converges.

[0059] Proof process: According to the alternating iterative algorithm, we can know is the feasible solution obtained by step 2 in the rth iteration, is the feasible solution obtained by step 2 in the r+1th iteration. According to the alternating iteration algorithm, we can also get is the feasible solution in step 3 of the rth iteration. For a given reflection coefficient vector In step 2, the function is solved to obtain the optimal solution, which is the beamforming matrix W r+1 Therefore, we know that: It is easy to find that the objective function in the proposed optimization problem is only related to the beamforming matrix W, so it can be concluded that: According to the above two formulas, we can get: In summary, the target value generated by the alternating iterative algorithm of the present 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 ensure convergence to the local optimal solution.

[0060] The advantages of this application scheme are specifically described below in combination with the simulation results: In the simulation, the specific deployment of the device is as follows: the transmitter consists of a uniform linear array located on the x-axis, and its reference antenna position is (0,0,0). The smart reflector consists of a uniform planar array located on the xy plane, and its reference reflector element position is (x R ,0,z R ). The target user is located in the xy plane, and its position is (x L ,y L ,0). The transmission distance between the transmitter and the target user is The transmission distance between the smart reflective surface and the target user is

[0061] Assume that there are two target users and multiple passive eavesdroppers. The location of target user 1 is (20m, 50m, 0), and the location of target user 2 is (480m, 50m, 0). There is an obstruction between the transmitter and target user 2. The minimum receiving SINR of the target users is equal, that is, γ1 = γ2 = γ = 10dB. The channel noise is equal, that is

[0062] like Figure 2 As shown in FIG. 1 , the curve of the transmission power of the confidential signal obtained by the alternating iterative algorithm changes with the number of iterations. As can be seen from the figure, the adopted alternating iterative algorithm converges quickly, and only 10 iterations are needed to obtain the minimum confidential signal transmission power and reach convergence.

[0063] like Figure 3 As shown, they represent the total received modulation symbol power of the two target users. Transmitter direct modulation symbol power RIS reflected modulation symbol power And the interference signal power Relationship with the minimum receiving SINR of the target user. As can be seen from the figure, target user 1 is close to the transmitter and mainly relies on the direct link of the transmitter to receive the signal. However, target user 2, due to the obstruction of the direct link of the transmitter, mainly relies on the reflection link of the smart reflector to receive the signal. At the same time, by optimizing the beamforming matrix, reflection coefficient matrix and artificial noise matrix, it is ensured that the receiving SINR of target user 1 and target user 2 meets the minimum requirement.

[0064] like Figure 4As shown, the relationship between the system security capacity of the two target users and the reflective elements of the intelligent reflective surface is respectively shown. For target user 1, the system security capacity corresponding to the solution of the present application is equal to the security capacity corresponding to the traditional frequency-controlled array solution, and both can ensure the secure transmission of information. For target user 2, the solution of the present application is significantly better than the traditional frequency-controlled array solution. With the increase in the number of reflective elements of the intelligent reflective surface, the security capacity of the solution based on the present application also increases, while the security capacity based on the traditional frequency-controlled array always remains at a low level. When there is an obstruction in the direct transmission link between the transmitter and the target user 2, the traditional frequency-controlled array security communication solution cannot guarantee that the target user 2 can reliably receive information, and the eavesdropper can steal confidential information by constantly approaching the transmitter.

[0065] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A non-line-of-sight multi-point physical layer information transmission device, characterized in that: Including a transmitter and a smart reflective surface; The process of the information transmission device sending information to the target user includes: The transmitter is used to adopt a modulation technology to modulate the code element information and load it onto the communication waveform signal, and transmit the communication waveform signal in the form of a beam to the smart reflection surface and the target user respectively; The intelligent reflection 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 reflection surface, obtain a comprehensive communication waveform signal, and extract code element information from the comprehensive communication waveform signal through demodulation technology.

2. The non-line-of-sight multi-point physical layer information transmission device according to claim 1, characterized in that: The transmitter is also used to add artificial noise to the communication waveform signal, specifically including: The transmitter modulates the code element information to obtain a modulation symbol vector; The transmitter adds artificial noise on the basis of the modulation symbol vector to obtain a transmission signal vector; The transmitter loads the transmission signal vector onto the communication waveform signal.

3. The non-line-of-sight multi-point physical layer information transmission device according to claim 2, characterized in that: The modulation symbol vector is: x=[x1, x2, ..., x v ,…,x V ] T ; In the formula, x v represents the modulation symbol corresponding to the vth target user, x v Satisfies: E(|x v | 2 )=1,x v ∈Φ, Φ is the modulation symbol set; The transmission signal vector is: Where P AN represents the emission energy of artificial noise, T AN represents the artificial noise matrix, and T AN ∈C N×N ;W represents the beamforming matrix, W∈C N×V , and W=[w1,w2,...,w v ,…,w V ] T , w v =[w v,1 ,w v,2 ,...,w v,n ,…,w v,N ] T , w v represents the vth modulation symbol x v An array of weight vectors.

4. The non-line-of-sight multi-point physical layer information transmission device according to claim 1, characterized in that: The integrated communication waveform signal comprises: In the formula, h AL,v represents the guidance vector of the transmitter to the vth target user, h AL,v ∈C N×1 ; h RL,v represents the array steering vector of the vth target user facing the intelligent reflection, h RL,v ∈C M×1 ; Φ represents the reflection coefficient vector of the smart reflective surface, θ m represents the phase shift reflection coefficient of the mth reflection element in the smart reflection surface, α represents the amplitude reflection coefficient, and α∈(0,1]; H1 represents the guidance matrix of the transmitter to the smart reflection surface, and H1∈C N×M ; s represents the transmitted signal vector of the transmitter, n L,v represents the channel additive white Gaussian noise received by the vth target user, and is the channel additive white Gaussian noise variance.

5. The non-line-of-sight multi-point physical layer information transmission device according to claim 1, characterized in that: It also includes a parameter optimization controller; the parameter optimization controller is used to optimize the beam forming matrix when the transmitter transmits a beam and the reflection coefficient vector when the smart reflection surface reflects a signal.

6. The non-line-of-sight multi-point physical layer information transmission device according to claim 5, characterized in that: The parameter optimization controller is used to construct a first optimization function with the goal of maximizing the artificial noise transmission power; is also used to rewrite the first optimization function into a second optimization function based on the total transmission power of the transmitter; and is also used to solve the beamforming matrix and the reflection coefficient vector respectively based on the second optimization function by using an alternating iterative algorithm; Wherein, the first optimization function comprises: In the formula, V represents the target user set; represents the set of all array weight vectors; γ v represents the minimum SINR requirement of the vth target user; The total transmission power of the transmitter is: Where P L,v Represents the modulation symbol x v The transmission power of The second optimization function comprises:

7. 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, adopts an alternating iterative algorithm to solve the beamforming matrix, specifically includes: Given a reflection coefficient vector And define the target user combined channel vector as Then the second optimization function is equivalently converted into a third optimization function; Wherein, the third optimization function includes: Introduce the autocorrelation matrix X v ∈C N×N ,and And set the matrix variable W v ≥0, rank(W v )=1, Get the transformation function: Introducing the transformation function into the third optimization function to obtain a fourth optimization function; Wherein, the fourth optimization function includes: The fourth optimization function is solved by using a convex optimization tool to obtain the beamforming matrix.

8. 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, adopts an alternating iterative algorithm to solve the beamforming matrix, specifically includes: Given a beamforming matrix W, the second optimization function is equivalently converted into a fifth optimization function; Wherein, the fifth optimization function includes: make in, Converting the fifth optimization function into a sixth optimization function; Wherein, the sixth optimization function includes: Introducing an auxiliary variable μ to convert the sixth optimization function into a seventh optimization function; Wherein, the seventh optimization function includes: In the formula, Introduce a matrix variable A and define an intermediate function, where the matrix variable A satisfies: A∈C (M+1)×(M+1) , A≥0, and rank(A)=1; intermediate functions include: Based on the intermediate function and the seventh optimization function, an eighth optimization function is obtained; Wherein, the eighth optimization function includes: Find A The eighth optimization function is solved using a convex optimization tool to obtain the reflection coefficient vector.

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