A MIMO secure communication method and system jointly assisted by DMA and RIS

Abstract

The invention discloses a MIMO secure communication method and system jointly assisted by DMA and RIS, belonging to the field of wireless communication. The method comprises the following steps: based on a transmission system model containing a base station, a user and an eavesdropper, a DMA model, a RIS model, a channel model and a communication model are constructed; by jointly optimizing beamforming vectors, RIS phase shift matrices and DMA weight matrices, under the constraints of maximum transmission power, phase shift unit mode constraints and phase shift Lorentz constraints, an optimization problem for improving confidentiality capacity is constructed, and an optimization model and constraint conditions are established; the optimization problem is divided into sub-problems of optimizing beamforming vectors, RIS phase shift matrices and DMA weight matrices by using a block coordinate descent method; in each iteration, the sub-problems of optimizing the beamforming vectors, RIS phase shift matrices and DMA weight matrices are solved in any order; iterate until convergence.

Description

Technical Field

[0001] The present invention relates to the field of wireless communications, and in particular to a DMA and RIS jointly assisted MIMO secure communication method and system. Background Art

[0002] Mobile communications have profoundly changed people's work and life, and greatly promoted the development of social economy. The popularization of the fifth generation mobile communication technology (5G) has led to a sharp increase in the number of wireless terminals, indicating that the Internet of Everything will flourish in the sixth generation mobile communication technology (6G) era, providing comprehensive support for the ubiquitous intelligent mobile industry. According to the International Telecommunication Union, by 2030, the number of global mobile broadband access users will increase to 17.1 billion, and the number of machine-type communication devices will reach 100 billion. This means that a large amount of high-security user privacy information is exposed in the wireless transmission environment, facing the risk of malicious eavesdropping and tampering, and the security challenges faced by wireless communication systems are becoming increasingly severe. The traditional upper-layer encryption mechanism requires a large amount of resources to be allocated for key generation, distribution and management, and cannot adapt to the trend of miniaturization and thinness of IoT devices. Therefore, it is particularly important to explore lightweight physical layer security transmission methods.

[0003] Physical layer security technology mainly uses the physical characteristics of wireless channels (noise, fading, and interference, etc.) and signal processing to achieve secure transmission. In recent years, the Reconfigurable Intelligent Surface (RIS) technology has emerged. It configures the wireless environment by adjusting the phase shift of a large number of passive and low-cost reflective elements on the surface and intelligently controls the propagation direction of the signal. Using RIS to create a signal propagation environment that is beneficial to legitimate users and unfavorable to eavesdroppers can effectively enhance physical layer security transmission.

[0004] In some existing technologies, for example, the Chinese patent application number 202410093668.9, "A RIS and DMA assisted multi-user MIMO downlink transmission joint design method and system (CN 117879740 A)", considers a downlink MIMO (Multiple-Input Mmultiple-Output) system, using DMA (Dynamic Metasurface Antenna) technology to replace the traditional antenna array at the base station end to reduce costs and power consumption, and using RIS's ability to regulate the propagation environment to improve the communication quality between the base station and the user, and by optimizing the transmit precoding matrix, RIS phase matrix and DMA weight matrix, improve the interference between multiple users. This invention does not take into account the security of information.

[0005] In other existing technologies, the implementation of the communication system mainly considers configuring a full digital antenna array at the base station end. As the number of antennas increases, the radio frequency link will cause high costs and huge power consumption.

[0006] Therefore, the existing technical solutions mainly have the following problems: 1) The research on DMA-assisted communication systems has not yet considered the issue of secure information transmission; 2) The RIS-assisted physical layer security transmission solution currently mainly considers configuring a fully digital antenna array at the base station end. As the number of antennas increases, the RF link will cause high costs and huge power consumption. Summary of the invention

[0007] In view of the deficiencies of the prior art, the present invention proposes a MIMO secure communication method and system jointly assisted by DMA and RIS.

[0008] The purpose of the present invention can be achieved through the following technical solutions:

[0009] A first aspect of the present invention relates to a MIMO secure communication method jointly assisted by DMA and RIS, comprising the following steps:

[0010] Based on a transmission system model including a base station, a user and an eavesdropper, a DMA model including a DMA weight matrix, a RIS model including a RIS phase shift matrix, a channel model, and a communication model characterizing the capacity of each channel are constructed; in the system model, the base station is configured with a DMA array, and a RIS is set between the base station and the user to provide a reflection link;

[0011] By jointly optimizing the beamforming vector, RIS phase shift matrix and DMA weight matrix, under the constraints of maximum transmit power, phase shift unit mode constraint and phase shift Lorentz constraint, an optimization problem to maximize the confidentiality capacity is constructed, and the optimization model and constraint conditions are established;

[0012] The optimization problem is divided into sub-problems of beamforming vector optimization, RIS phase shift matrix optimization and DMA weight matrix optimization by using block coordinate descent method;

[0013] In the subproblem of beamforming vector optimization, the RIS phase shift matrix and DMA weight matrix are fixed; in the subproblem of RIS phase shift matrix optimization, the beamforming vector and DMA weight matrix are fixed; in the subproblem of DMA weight matrix optimization, the beamforming vector and RIS phase shift matrix are fixed;

[0014] In each iteration, the sub-problems of beamforming vector optimization, RIS phase shift matrix optimization and DMA weight matrix optimization are solved in any order, and the optimization results of the beamforming vector, RIS phase shift matrix or DMA weight matrix obtained each time are brought into the optimization of the next sub-problem as update values; iterate until convergence.

[0015] Optionally, in the channel model, a Rayleigh fading model is introduced to model the channel and derive the confidentiality capacity.

[0016] Optionally, the objective functions and constraints in the sub-problems of beamforming vector optimization, RIS phase shift matrix optimization and DMA weight matrix optimization are converted into convex forms by a continuous convex approximation algorithm;

[0017] The sub-problem of RIS phase shift matrix optimization is solved by using the principal component-maximum algorithm.

[0018] Optionally, the phase shift Lorentz constraint is relaxed to a pure phase weight constraint with constant amplitude and arbitrary phase by a constant amplitude method.

[0019] Optionally, the iteration specifically includes the following steps:

[0020] According to the optimization model, given the beamforming vector, the RIS phase shift matrix and the DMA weight matrix, the confidentiality capacity is calculated, and the optimized relaxation variables are calculated;

[0021] According to the optimization model, given the optimized relaxation variables, RIS phase shift matrix and DMA weight matrix, the optimized beamforming vector is calculated;

[0022] According to the optimization model, given the optimized relaxation variables, the DMA weight matrix and the optimized beamforming vector, the optimized RIS phase shift matrix is ​​calculated;

[0023] According to the optimization model, given the optimized slack variables, the optimized beamforming vectors and the optimized RIS phase shift matrix, an optimized DMA weight matrix is ​​calculated.

[0024] A second aspect of the present invention relates to a MIMO secure communication system jointly assisted by DMA and RIS, comprising:

[0025] A base station, configured with a DMA array;

[0026] RIS, set between the user and the base station, is used to provide a reflection link;

[0027] A basic model building module, used to build a DMA model including a DMA weight matrix, a RIS model including a RIS phase shift matrix, a channel model, and a communication model characterizing the capacity of each channel;

[0028] An optimization problem construction module is used to construct an optimization problem for maximizing confidentiality capacity by jointly optimizing beamforming vectors, RIS phase shift matrices, and DMA weight matrices under the constraints of maximum transmit power, phase shift unit mode constraints, and phase shift Lorentz constraints, and to establish optimization models and constraints.

[0029] The block coordinate descent algorithm module divides the optimization problem into sub-problems of beamforming vector optimization, RIS phase shift matrix optimization and DMA weight matrix optimization by block coordinate descent method; in the sub-problem of beamforming vector optimization, the RIS phase shift matrix and the DMA weight matrix are fixed; in the sub-problem of RIS phase shift matrix optimization, the beamforming vector and the DMA weight matrix are fixed; in the sub-problem of DMA weight matrix optimization, the beamforming vector and the RIS phase shift matrix are fixed;

[0030] And, a sub-problem solving module solves the sub-problems of beamforming vector optimization, RIS phase shift matrix optimization and DMA weight matrix optimization in any order, and the optimization results of the beamforming vector, RIS phase shift matrix or DMA weight matrix obtained each time are brought into the optimization of the next sub-problem as update values; iterate until convergence.

[0031] Optionally, in the channel model, a Rayleigh fading model is introduced to model the channel and derive the confidentiality capacity.

[0032] Optionally, the phase shift Lorentz constraint is relaxed to a pure phase weight constraint with constant amplitude and arbitrary phase by a constant amplitude method.

[0033] Optionally, the iteration specifically includes the following steps:

[0034] According to the optimization model, given the beamforming vector, the RIS phase shift matrix and the DMA weight matrix, the confidentiality capacity is calculated, and the optimized relaxation variables are calculated;

[0035] According to the optimization model, given the optimized relaxation variables, RIS phase shift matrix and DMA weight matrix, the optimized beamforming vector is calculated;

[0036] According to the optimization model, given the optimized relaxation variables, the DMA weight matrix and the optimized beamforming vector, the optimized RIS phase shift matrix is ​​calculated;

[0037] According to the optimization model, given the optimized slack variables, the optimized beamforming vectors and the optimized RIS phase shift matrix, an optimized DMA weight matrix is ​​calculated.

[0038] A third aspect of the present invention relates to a wireless communication device configured with the above-mentioned DMA and RIS jointly assisted MIMO secure communication system.

[0039] Specifically, the present invention establishes a RIS and DMA-assisted downlink MIMO wireless security transmission model, which is equipped with a DMA antenna array on the base station side and deploys RIS between the base station and the user and the eavesdropper to provide a reflection link. It uses the low cost of DMA and the intelligent control advantages of RIS on the channel environment to provide a physical layer security communication solution with superior performance and low cost for large-scale MIMO systems.

[0040] The problem of optimizing the confidentiality performance is studied for the MIMO system assisted by RIS and DMA arrays. Since Alice, Bob and RIS are in each other's far field, the Rayleigh channel is introduced to model the channel of the system, and the confidentiality capacity is derived based on this model. In order to solve the base station digital beamforming vector, DMA weight matrix and RIS phase shift matrix, the BCD method and slack variables are used to restate the objective function, and the problem of maximizing the confidentiality capacity is transformed into the optimization sub-problems of beamforming, RIS phase shift matrix and DMA weight matrix. An alternating iterative solution algorithm is proposed, which can achieve a larger confidentiality capacity.

[0041] Beneficial effects of the present invention:

[0042] The present invention provides a RIS and DMA assisted downlink MIMO secure transmission system model, which makes full use of the flexible antenna architecture of DMA and the intelligent control capability of RIS to improve the security of information transmission from the physical layer. Compared with the traditional model based on all-digital array antenna, the proposed model can further improve the performance of the system under low power consumption and low cost, and flexibly meet the communication needs in different scenarios.

[0043] Based on the provided model, the present invention proposes a problem of jointly optimizing the transmit beamforming, RIS phase shift matrix and DMA weight matrix. In order to solve this non-convex problem, it is first converted into a more tractable form based on MMSE, and then decomposed into three sub-problems, which are iteratively solved by the block coordinate descent method. In each iteration, the beamforming, RIS phase shift matrix and DMA weight matrix are solved by the Successive Convex Approximation (SCA) and MM algorithm. The proposed algorithm comprehensively considers the energy consumption requirements and the target performance detection requirements, and can significantly improve the confidentiality capacity of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The present invention will be further described below in conjunction with the accompanying drawings.

[0045] Figure 1 A schematic diagram of a hybrid RIS and DMA-assisted secure MIMO transmission system constructed in the first step in an embodiment of the present application;

[0046] Figure 2 A schematic diagram of the relationship between confidentiality capacity and transmission power in an embodiment of the present application;

[0047] Figure 3 It is a schematic diagram of the change of confidentiality capability with the number of RIS reflective elements in the embodiment of the present application. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] In some embodiments of the present invention, a DMA and RIS jointly assisted MIMO secure communication method is disclosed.

[0050] Step 1: Establish system model:

[0051] Figure 1The hybrid RIS and DMA-assisted secure MIMO transmission system in this paper consists of a base station (BS) named Alice, a user (Bob), and an eavesdropper (Eve). Considering the urban environment, it is assumed that the direct link between Alice and Bob / Eve is blocked by an obstacle (Obstacle). The BS is equipped with a DMA array and a RIS is deployed between Alice and Bob to provide a reflection link. In this model, the RIS consists of N reflection elements, and Alice, Bob, and Eve are equipped with U, and The channels from Alice to RIS, from RIS to Bob, and from RIS to Eve are , , Represents, where C represents the complex number field.

[0052] (1) DMA model

[0053] The DMA array installed on the BS consists of L microstrips, each of which contains M metamaterial units, so the total number of metamaterial units is The input signal of each microstrip can be expressed as: x = ws where w∈ Denotes the corresponding digital beamforming, and s denotes the information-carrying symbol with normalized power. Then, the output radiation observed at the DMA can be expressed as: y = FDx where D∈ is a configurable DMA weight matrix, which can be expressed as: in Indicates the matrix The weight coefficient of the row and column n, Indicates The first microstrip The frequency responses of the components are given by: In addition, F is a diagonal matrix, expressed as . Use The first microstrip The propagation effect of each element is ,in , are the waveguide attenuation and waveguide derivative, respectively. is an imaginary unit, Indicates the first Microstrip The phase shift of the elements.

[0054] (2) The RIS model system deploys a RIS consisting of N reflection units at the user site, each of which can autonomously adjust the phase of the incident signal. , , represents the phase shift matrix of RIS, where represents a diagonal matrix, where the diagonal elements are all elements in the vector x, i.e., the reflection coefficients, and the off-diagonal elements are all 0.

[0055] (3) Channel Model For simplicity, it is assumed that Alice, Bob, Eve, and RIS are in each other's far field. In addition, a general Rayleigh fading model is considered, so the channel from Alice to RIS is: K is the calculation factor, is the path loss from Alice to RIS, and are the Line of Sight (LoS) and Non Line of Sight (NLoS) components between Alice and RIS. And: in represents a complex Gaussian distribution with mean 0 and variance 1, and All represent array responses.

[0056] in is the conjugate transpose of X, λ is the wavelength, represents the antenna spacing at Alice, is the component spacing at the RIS. and are the elevation and azimuth of Alice's emission angle, and are the elevation and azimuth of the RIS arrival angle. and are the elevation and azimuth of Bob's angle of arrival. Indicates the number of RIS columns, Indicates the number of RIS rows.

[0057] Similarly, the channel from RIS to Bob is: The channel from RIS to Eve is: and is the path loss from RIS to Bob, , are the line-of-sight and non-line-of-sight components of RIS and Bob, respectively. , They represent the elevation and azimuth angles reaching Bob respectively; is the path loss from RIS to Eve, , They are the line-of-sight and non-line-of-sight components of RIS and Eve, respectively.

[0058] (4) Communication Model The signals received at Bob and Eve can be expressed as: in and are Gaussian white noise at Bob and Eve respectively.

[0059] The channel capacities from Alice to Bob and from Alice to Eve are given by: in represents the logarithmic function, det(x) represents the determinant operation of x, represents the conjugate transpose of x, represents the noise variance received by user Bob, represents the noise variance received by the eavesdropper Eve, I represents the identity matrix, the I subscript represents the dimension of the identity matrix, and the equivalent channels to the indirect links of Bob and Eve are: , .

[0060] Step 2: Constructing the confidentiality of the optimization problem system can be done by {C}_{S}=\left [ {{C}_{B}-{C}_{E}} \right ]^{+} Get, where \left [ {X} \right ]^{+} Indicates that the positive part of x is taken, thereby ensuring that the confidentiality capacity is a non-negative value. In this embodiment, the purpose is to maximize the confidentiality capacity under the maximum transmit power constraint, the phase shift unit mode constraint and the phase shift Lorentz constraint by jointly optimizing the reflection phase shift matrix at the beamformer, RIS and DMA, which can be expressed as: in represents the second norm of x, constraint C1 is the power constraint, P max is the maximum transmit power, C2 is the Lorentz response constraint of the weight matrix in DMA, which is a non-convex constraint, and C3 is the RIS matrix phase modulus constraint. Due to the coupling between variables and the modulus-one constraint, this problem is a non-convex problem. To make the constraints easier to handle, problem P1 is transformed as follows: This problem places a power constraint on the digital beamforming vector rather than on the entire transmitted signal.

[0061] Step 3: Design a solution algorithm for the optimization problem

[0062] By using the Block Coordinate Descent (BCD) method, the objective function is first reformulated as follows: in yes 1 / 2 of .

[0063] make Represents the equivalent receiving matrix. The minimum mean square error (MMSE) of the received signal after passing through the linear decoder is: By introducing slack variables >0, , is equivalent to: The best of them , It is given by the following expression: in represents the inverse operation of x, for The inverse of , restate for: Where Tr(x) represents the trace of x, is the solution of the slack variable; the objective function can be rewritten as follows: The overall steps of the algorithm for maximizing confidentiality capacity are as follows: First, given , , , and , optimize the beamforming vector w. Then, using the given , , , and w to update the RIS phase shift matrix Next, use the given , , , and w update the weight matrix Finally, using the given w, and renew , and , and iteratively repeat the same process until convergence.

[0064] (1) Fixed , , optimize the beamforming vector w, then P3 can be written as: in: is a constant, so the problem can be rewritten as: This problem is a convex problem and the constraints are convex constraints. This type of problem can be solved efficiently using the CVX toolkit.

[0065] (2) Fixed w, D, Optimization , then P3 can be written as: in: is a constant, so the original problem can be transformed into: set up , ,\phi =\left [ {{e}^{{j\varphi}_{1}},...,{e}^{{j\varphi}_{N}}} \right ]^{T}=\left [ {{\phi}_{1},...,{\phi}_{N}} \right ]^{T} ,g=\left [ {{G}_{(1,1)},...,{G}_{(N,N)}} \right ]^{T} Respectively , The diagonal elements of . Definition It refers to the Hadamard product. The Hadamard product of matrices B and C is defined as the product of the corresponding positions of the two and is converted to: in represents the conjugate operation, so The problem can be transformed into: in represents the real part operation. The problem can be transformed into: in , the optimal solution to the problem is: in, is a matrix The maximum eigenvalue of Indicates complex number The amplitude of is a vector that changes with the number of iterations t in MM. Based on the above discussion, when the MM algorithm converges, the optimal phase shift can be obtained.

[0066] (3) Fixed ,w, optimize the DMA weight matrix D, then P3 can be written as: in: , The matrix D and the beamforming vector w are transformed into a diagonal matrix .therefore can be restated as: in: is a constant, is to write each element of w as M, and turn it into a vector with LM elements. Therefore, the original problem can be rewritten as: To solve this problem, the constant amplitude method is used to relax the Lorentz constraint into a pure phase weight constraint with constant amplitude and arbitrary phase, which is given by: definition And using the matrix identities we get: in is equivalent to mapping each element in d to the nearest point on the Lorentz constraint circle, so that Microstrip The configuration phase of a metamaterial element can be obtained by the following formula: in represents the absolute value operation of x, and the above formula can be easily solved using a one-dimensional search.

[0067] Step 4: Implementation of optimization algorithm

[0068] 1. Optimize phase MM algorithm:

[0069] S10: Assume the initial number of iterations t=1 and the accuracy ε . Enter a possible solution , the value of the objective function in problem M1 is ; S20: Calculation S30: Update M2 S40: Calculate the objective function ,if If established, terminate; otherwise, set And go to step S20.

[0070] 2. For the three sub-problems, joint optimization is used , , BCD algorithm for three variables.

[0071] S10: Initialization iteration number , maximum number of iterations , the initial parameters are , and , the iteration accuracy is ε , calculate the .

[0072] S20: Given , and , calculate the confidentiality capacity , and calculate the , and .

[0073] S30: Given , , , and Optimize by solving problem BCD2 .

[0074] S40: Given , , , and Optimize by solving problem BCD3 .

[0075] S50: Given , , , and Optimize by solving problem BCD4 .

[0076] S60: If > or < Otherwise, set And return to step 2.

[0077] In some specific embodiments, a Matlab platform is used to perform simulation experiments to evaluate the confidentiality capacity of the system, the performance of DMA, and the performance of RIS.

[0078] exist Figure 2In the paper, the number of RIS reflective elements is fixed to 36, the number of microstrips of the DMA array and the number of elements on each microstrip are set to (8,8) and (6,6), and the number of antennas deployed on the Bob and Eve nodes is considered to be 25 and 9. The data results show that the confidentiality capacity increases with the increase of the transmission power. This is because with the increase of the transmission power, the signal strength also increases, which can improve the signal-to-noise ratio of the signal. By adjusting the phase of the RIS surface reflection unit, beamforming can be achieved to enhance the signal strength of the user in the target direction. When the DMA array parameters are set to (8,8), the confidentiality capacity is large. This is because increasing the number of microstrips and the number of elements on the microstrips of the DMA array can increase the degree of freedom of the system, so that the transmission direction and strength of the signal can be adjusted more flexibly. When more antennas are deployed on the Bob node, the confidentiality capacity is improved. On the contrary, when more antennas are deployed on the Eve node, the confidentiality capacity decreases. This is because the increase in the number of antennas can improve the signal reception capability.

[0079] exist Figure 3 In the figure, the variation of confidentiality capability with the number of RIS reflective elements is provided, and the transmit power is set to 10dBm, 15dBm, 20dBm, and 25dBm respectively. The results show that the higher the transmit power, the stronger the confidentiality capability, and the confidentiality capacity increases with the increase in the number of RIS reflective elements. This is because the increase in the number of RIS reflective elements can enhance the beamforming capability, thereby improving the signal-to-noise ratio of the received signal.

[0080] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0081] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. A MIMO secure communication method jointly assisted by DMA and RIS, characterized in that: The following steps are involved: Based on the transmission system model including base stations, users and eavesdroppers, a DMA model including a DMA weight matrix, a RIS model including a RIS phase shift matrix, a channel model, and a communication model representing the capacity of each channel are constructed; In the system model, the base station is equipped with a DMA array, and a RIS is set between the base station and the user to provide a reflection link; by jointly optimizing the beamforming vector, the RIS phase shift matrix and the DMA weight matrix, under the maximum transmission power constraint, the phase shift unit mode constraint and the phase shift Lorentz constraint, an optimization problem for maximizing the confidentiality capacity is constructed, and an optimization model and constraint conditions are established; the block coordinate descent method is used to divide the optimization problem into sub-problems of beamforming vector optimization, RIS phase shift matrix optimization and DMA weight matrix optimization; in the sub-problem of beamforming vector optimization, the RIS phase shift matrix and the DMA weight matrix are fixed, and in the sub-problem of RIS phase shift matrix optimization, the beamforming vector and the DMA weight matrix are fixed; in the sub-problem of DMA weight matrix optimization, the beamforming vector and the RIS phase shift matrix are fixed; in each iteration, the sub-problems of beamforming vector optimization, RIS phase shift matrix optimization and DMA weight matrix optimization are solved in any order, and the optimization results of the beamforming vector, RIS phase shift matrix or DMA weight matrix obtained each time are brought into the optimization of the next sub-problem as update values; iteration is performed until convergence.

2. The MIMO secure communication method jointly assisted by DMA and RIS according to claim 1, characterized in that: In the channel model, a Rayleigh fading model is introduced to model the channel and derive the confidentiality capacity.

3. The DMA and RIS-assisted MIMO secure communication method according to claim 1, characterized in that: The objective functions and constraints in the sub-problems of beamforming vector optimization, RIS phase shift matrix optimization and DMA weight matrix optimization are converted into convex forms through a continuous convex approximation algorithm; the sub-problem of RIS phase shift matrix optimization is solved using a principal component-maximum algorithm.

4. The DMA and RIS-assisted MIMO secure communication method according to claim 1, characterized in that: The phase shift Lorentz constraint is relaxed to a pure phase weight constraint with constant amplitude and arbitrary phase by the constant amplitude method.

5. The DMA and RIS-assisted MIMO secure communication method according to claim 1, characterized in that: The iteration specifically includes the following steps: according to the optimization model, given the beamforming vector, RIS phase shift matrix and DMA weight matrix, calculating the confidentiality capacity and calculating the optimized slack variables; according to the optimization model, given the optimized slack variables, RIS phase shift matrix and DMA weight matrix, calculating the optimized beamforming vector; according to the optimization model, given the optimized slack variables, DMA weight matrix and optimized beamforming vector, calculating the optimized RIS phase shift matrix; according to the optimization model, given the optimized slack variables, optimized beamforming vector and optimized RIS phase shift matrix, calculating the optimized DMA weight matrix.

6. A MIMO secure communication system jointly assisted by DMA and RIS, characterized in that: include: A base station, configured with a DMA array; RIS, set between the user and the base station, is used to provide a reflection link; The basic model construction module is used to construct a DMA model including a DMA weight matrix, a RIS model including a RIS phase shift matrix, a channel model, and a communication model that characterizes the capacity of each channel; the optimization problem construction module is used to construct an optimization problem that maximizes the confidentiality capacity under the maximum transmit power constraint, the phase shift unit mode constraint, and the phase shift Lorentz constraint by jointly optimizing the beamforming vector, the RIS phase shift matrix, and the DMA weight matrix, and establish the optimization model and constraint conditions; A block coordinate descent algorithm module divides the optimization problem into sub-problems of beamforming vector optimization, RIS phase shift matrix optimization and DMA weight matrix optimization by block coordinate descent method; in the sub-problem of beamforming vector optimization, the RIS phase shift matrix and the DMA weight matrix are fixed; in the sub-problem of RIS phase shift matrix optimization, the beamforming vector and the DMA weight matrix are fixed; in the sub-problem of DMA weight matrix optimization, the beamforming vector and the RIS phase shift matrix are fixed; and a sub-problem solving module solves the sub-problems of beamforming vector optimization, RIS phase shift matrix optimization and DMA weight matrix optimization in any order, and the optimization result of the beamforming vector, RIS phase shift matrix or DMA weight matrix obtained each time is brought into the optimization of the next sub-problem as an update value; iterate until convergence.

7. The DMA and RIS jointly assisted MIMO secure communication system according to claim 6, characterized in that: In the channel model, a Rayleigh fading model is introduced to model the channel and derive the confidentiality capacity.

8. The DMA and RIS jointly assisted MIMO secure communication system according to claim 6, characterized in that: The phase shift Lorentz constraint is relaxed to a pure phase weight constraint with constant amplitude and arbitrary phase by the constant amplitude method.

9. The DMA and RIS jointly assisted MIMO secure communication system according to claim 6, characterized in that: The iteration specifically includes the following steps: according to the optimization model, given the beamforming vector, RIS phase shift matrix and DMA weight matrix, calculating the confidentiality capacity and calculating the optimized slack variables; according to the optimization model, given the optimized slack variables, RIS phase shift matrix and DMA weight matrix, calculating the optimized beamforming vector; according to the optimization model, given the optimized slack variables, DMA weight matrix and optimized beamforming vector, calculating the optimized RIS phase shift matrix; according to the optimization model, given the optimized slack variables, optimized beamforming vector and optimized RIS phase shift matrix, calculating the optimized DMA weight matrix.

10. A wireless communication device, characterized in that: A MIMO secure communication system jointly assisted by DMA and RIS as claimed in any one of claims 6 to 9 is provided.

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