STAR-RIS-Assisted Secure Communication Method, Device, and Medium Against Cooperative Multi-Eavesdropping

Abstract

A STAR-RIS assisted secure communication method, device and medium for countering cooperative multi-eavesdropping in the present invention solve the problem of improving the system sum-security rate in the case where multiple malicious users cooperate with each other to eavesdrop on legitimate users in a communication system. The present invention includes: S1, initializing the beamforming vectors of each legitimate user and the transmission-reflection coefficients of the STAR-RIS; S2, fixing the transmission-reflection coefficients, constraining the rate upper bound of malicious eavesdropping users, and obtaining the beamforming vectors by maximizing the legitimate user rate; S3, fixing the beamforming vectors, relaxing the feasible region of the transmission-reflection coefficients, and obtaining the solution of the transmission-reflection coefficients by using the penalty concave-convex process; S4, repeating S2 and S3 until the system sum-security rate converges. The present invention is applicable to a STAR-RIS assisted secure communication system in a cooperative multi-eavesdropping scenario, can cover general single-eavesdropping models and independent multi-eavesdropping models, and improves the system sum-security rate.

Description

Technical Field

[0001] The present invention relates to the field of communication technologies, and particularly to a STAR-RIS assisted secure communication method, device, and storage medium for countering collaborative multi-eavesdropping. Background Art

[0002] Traditional reconfigurable intelligent surfaces (RISs) can only cover their reflection intervals, which limits their application flexibility and electromagnetic propagation adjustment capabilities. In this context, a RIS that can simultaneously transmit and reflect (STAR-RIS) has been proposed, which can cover the entire space range and expand its application scenarios. However, the unique ability of STAR-RIS to reconfigure the entire space radio propagation environment will inevitably lead to full-space eavesdropping. That is, eavesdroppers located on either side of the STAR-RIS can obtain the confidential information passing through the STAR-RIS.

[0003] In the existing research on physical layer security, in most scenarios, it is considered that eavesdroppers independently decode the confidential information of legitimate users. However, in actual networks, eavesdroppers usually cooperate with each other to jointly decode the confidential information. The full-space eavesdropping problem introduced by STAR-RIS requires optimizing the minimum security rate when users are eavesdropped by all eavesdroppers, and the cooperation among eavesdroppers introduces new non-convexity in the optimization problem, making the existing algorithms no longer applicable. Therefore, a new solution is needed to improve the security of wireless communication networks. Summary of the Invention

[0004] A STAR-RIS assisted secure communication method, device, and storage medium for countering collaborative multi-eavesdropping proposed by the present invention are used to solve the problem of existing eavesdroppers cooperating to eavesdrop on the confidential information of legitimate users.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A STAR-RIS assisted secure communication method for countering collaborative multi-eavesdropping includes the following steps:

[0007] S1. Initialize the beamforming vectors of each legitimate user and the transmission and reflection coefficients of the STAR-RIS;

[0008] S2. Fix the transmission and reflection coefficients, constrain the rate upper bound of malicious eavesdropping users, and obtain the beamforming vectors by maximizing the rate of legitimate users;

[0009] S3. Fix the beamforming vectors, relax the feasible region of the TARCs, and use the penalty concave-convex procedure to obtain the solutions of the TARCs;

[0010] S4. Repeat S2 and S3 until the security rate of the system converges.

[0011] On the other hand, the present invention also discloses a computer-readable storage medium storing a computer program, which when executed by a processor causes the processor to execute the steps of the above method.

[0012] On yet another aspect, the present invention also discloses a computer device, including a memory and a processor, where the memory stores a computer program, which when executed by the processor causes the processor to execute the steps of the above method.

[0013] As can be seen from the above technical solutions, the STAR-RIS-assisted secure communication method for counteracting collaborative multi-eavesdropping of the present invention can be used in scenarios where there are multiple eavesdroppers and they cooperate with each other. This solution can effectively improve the secure communication rate of users and ensure the security of the communication system under the limitation of a certain transmission power.

[0014] The present invention specifically discloses a secure transmission scheme for counteracting collaborative multi-eavesdropping assisted by a simultaneously transmitting and reflecting intelligent surface (STAR-RIS), which mainly solves the problem of improving the system sum and secure rate in the case where multiple malicious users in a communication system cooperate to eavesdrop on legitimate users. The implementation steps are as follows: 1. Initialize the beamforming vectors of each legitimate user and the transmission and reflection coefficients (TARCs) of the STAR-RIS; 2. Fix the transmission and reflection coefficients of the STAR-RIS, constrain the rate upper bound of malicious eavesdropping users, and obtain the beamforming vectors by maximizing the rate of legitimate users; 3. Fix the beamforming vectors, relax the feasible region of the TARCs, and use the penalty concave-convex process to obtain the solution of the TARCs. 4. Alternately execute the second and third steps to gradually increase the system sum and secure rate until convergence. Simulation experiments verify the effectiveness of this scheme.

[0015] The present invention considers a secure transmission scheme for STAR-RIS-assisted counteracting collaborative eavesdropping, and alternately optimizes the beamforming vectors of the base station and the transmission and reflection coefficients of the STAR-RIS under a certain transmission power constraint to improve the system sum and secure rate. In the present invention, to solve the non-convexity of the secure rate, first, convex approximations are made for the rates of legitimate users and eavesdroppers to obtain their lower and upper bounds respectively, and then auxiliary variables are introduced to equivalently process the minimum secure rate. At the same time, to handle the non-convexity of the transmission and reflection coefficients, slack variables are introduced to make a convex approximation for them. The simulation results verify the performance of the proposed scheme and show an improvement over the existing schemes.

[0016] Specifically, compared with the prior art, the advantages of the present invention include:

[0017] 1. The present invention is applicable to a STAR - RIS - assisted secure communication system in a cooperative multi - eavesdropping scenario. This system model covers general single - eavesdropping models and independent multi - eavesdropping models, improving the sum - security rate of the system.

[0018] 2. Compared with existing other solutions, the present invention can achieve a higher sum - security rate of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a conceptual scenario diagram of the present invention;

[0020] Figure 2 It is a convergence diagram of the algorithmic solution proposed by the present invention and the comparative solution;

[0021] Figure 3 It is a comparison of sum - security rates under different transmission powers;

[0022] Figure 4 It is a comparison of sum - security rates under different numbers of STAR - RIS elements;

[0023] Figure 5 It is a flowchart of the method of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention.

[0025] As Figure 5 shown, the STAR - RIS - assisted secure communication method for counteracting cooperative multi - eavesdropping described in this embodiment includes the following steps.

[0026] Consider a STAR - RIS - assisted secure communication system, which includes a base station with M antennas and a STAR - RIS with N elements. There is a legitimate user in each of the transmission area and the reflection area of the STAR - RIS. There are several cooperating eavesdroppers around each legitimate user, and there are a total of eavesdroppers. Due to the regional separation, the eavesdroppers in the two areas cannot cooperate with each other. Let the channels from the base station to the STAR - RIS, from the STAR - RIS to the th legitimate user, from the STAR - RIS to the th eavesdropper, from the base station to the th legitimate user, and from the base station to the th eavesdropper be , , , , , where , , and are the set of legitimate users and the set of eavesdroppers respectively, is the set of complex numbers. The base station broadcasts a signal , where is the power-normalized signal sent by the base station to the k -th user. is the beamforming vector. Subject to the maximum transmit power limit of the base station, must satisfy . Let represent the transmission coefficient matrix and reflection coefficient matrix of the STAR-RIS, where , , is the transmission area, is the reflection area; then the received signal of the -th user and the received signal of the -th eavesdropper are respectively

[0027] (1)

[0028] (2)

[0029] where is the mapping of the user / eavesdropper to its area. If the -th legitimate user is in the transmission area of the STAR-RIS, then , if in the reflection area, then . and are respectively the received noise of the -th user and the -th eavesdropper, and both follow the complex Gaussian distribution .

[0030] Let , , then the achievable rate of the -th legitimate user is

[0031] (3)

[0032] While the achievable rate of the eavesdroppers located in the ξ area collaborating to eavesdrop on the -th legitimate user is

[0033] (4)

[0034] where , is the set of eavesdroppers located in the ξ area. Considering that an eavesdropper located in any area can eavesdrop on the signals of two users located in the transmission area and the reflection area at the same time, the -th user's secure rate is , where . Therefore, the following optimization problem needs to be solved for this secure communication system:

[0035] (5a)

[0036] (5b)

[0037] (5c)

[0038] (5e)

[0039] (5d)

[0040] (5e)

[0041] where .

[0042] Step 1 Initialize the beamforming vectors of each legitimate user and the transmission and reflection coefficients of the STAR-RIS, and make the beamforming vectors and transmission and reflection coefficients satisfy the constraint conditions of the optimization problem (5).

[0043] Step 2 Fix the transmission and reflection coefficients and optimize the beamforming vectors. The specific implementation method is as follows:

[0044] Perform a first-order Taylor expansion on the rates of the legitimate users and eavesdroppers. At the fixed point , there are and lower and upper bounds of

[0045] (6)

[0046] (7)

[0047] where

[0048] (8)

[0049] (9)

[0050] (10)

[0051] (11)

[0052] (12)

[0053] (13)

[0054] (14)

[0055] To take the real part. The optimization objective is transformed into , and at this time the optimization objective is still non-convex. Further introduce auxiliary variables and , and we can get The upper bound of

[0056] (15)

[0057] where

[0058] (16)

[0059] (17)

[0060] (18)

[0061] At this time is a quadratic divided by a linear function and is a convex function.

[0062] To smooth the objective function, ignore , and transform the problem of optimizing the beamforming vector into

[0063] (19a)

[0064] (19b)

[0065] (19c)

[0066] The above problem is a convex problem and can be solved using the CVX toolbox.

[0067] Step 3: Fix the beamforming vector and optimize the transmission and reflection coefficients. The specific implementation method is as follows:

[0068] For the non-convex constraints (5c) and (5d), they are equivalently transformed into ; and the non-convex constraint (5e) can be equivalently transformed into

[0069] (20)

[0070] Introduce a slack variable , and relax the feasible region to

[0071] (21)

[0072] (22)

[0073] (23)

[0074] (24)

[0075] The constraint (22) is still non-convex. Further, at the fixed point perform a first-order Taylor expansion on the left side of equation (22) to obtain

[0076] (25)

[0077] By introducing a penalty term to approximate the original constraint, the sub-problem of optimizing the transmit-reflection coefficient can be transformed into

[0078] (26a)

[0079] (26b)

[0080] After each iteration of optimization it is necessary to update , that is, the used at the th iteration, where , and then continue to optimize until is less than the target accuracy.

[0081] Step 4 repeats Steps 2 and 3 for alternating optimization until the sum-rate and security rate converge.

[0082] As Figure 5 shown, the overall algorithm process includes:

[0083] First, initialize the optimization variables , , and , and then alternately optimize the beamforming vector and the transmit-reflection coefficient until convergence.

[0084] The method in the embodiments of the present invention will be described below in conjunction with specific embodiments for simulation verification

[0085] In the experimental scenario, the coordinates of the base station and the STAR-RIS in three-dimensional space are (0, 0, 10) and (0, 70, 5) respectively, and the coordinates of the legitimate users are (-10, 70, 0) and (10, 70, 0) respectively. The base station is equipped with 8 antennas. Eavesdroppers are randomly generated within a range of 5 meters from the legitimate users, with 3 eavesdroppers around each legitimate user. The channels from the base station to the STAR-RIS and from the base station to the users and eavesdroppers are Rice channels, modeled as , where when , and are the path loss factor and the Rice factor respectively. The path loss factors of the channels from the base station to the STAR-RIS, from the STAR-RIS to the legitimate users / eavesdroppers, and from the base station to the legitimate users / eavesdroppers are 2.2, 2.5, and 3.5 respectively, . And the channels from the base station to the legitimate users / eavesdroppers are Rayleigh channels. The power of the additive white Gaussian noise . The experiment uses the Monte Carlo method, randomly generating the positions of the eavesdroppers and the channel parameters 1000 times and performing optimization, and then taking the average of the sum and the secrecy rate obtained after each optimization as the system security performance.

[0086] Experimental content

[0087] (1) According to the above simulation experimental scenario, complete the modeling in MATLAB, and write the corresponding scheme algorithm code to complete the convergence experiment.

[0088] (2) Change the upper limit of the transmit power, with other variables unchanged, and show the influence of the upper limit of the transmit power on the whole system and the secrecy rate through comparison.

[0089] (3) Change the number of elements of the STAR-RIS, with other variables unchanged, and show the influence of the number of elements of the STAR-RIS on the whole system and the secrecy rate through comparison.

[0090] (4) To verify whether the proposed scheme has excellent performance, conduct multiple sets of control experiments for testing.

[0091] Experimental results

[0092] Figure 2 shows the convergence situations of the proposed scheme of the present invention and the comparative scheme at different transmit powers. It can be seen that the convergence speed of the algorithm proposed by the present invention is faster than that of the comparative scheme.

[0093] Figure 3Show the comparison of the sum secure rate under different transmit powers. It can be seen that as the upper limit of the transmit power increases, the sum secure rate of this scheme increases accordingly. Moreover, this scheme has advantages compared with the schemes without RIS, traditional RIS, and PDD-BSUM schemes, and can still maintain good performance with 4-bit discrete phase shifts. Although the performance gap between the PDD-BSUM scheme and this scheme decreases at higher transmit powers, according to Figure 2 the results, this scheme has a faster convergence rate at higher transmit powers and still has advantages compared with the PDD-BSUM scheme.

[0094] Figure 4 Show the comparison of the sum secure rate under different numbers of STAR-RIS elements. It can be seen that as the number of STAR-RIS elements increases, the sum secure rate of this scheme increases accordingly. This scheme has advantages compared with each scheme and can still maintain good performance with 4-bit discrete phase shifts.

[0095] On the other hand, the present invention also discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to execute the steps of the above method.

[0096] On yet another aspect, the present invention also discloses a computer device including a memory and a processor, where the memory stores a computer program, which, when executed by the processor, causes the processor to execute the steps of the above method.

[0097] In another embodiment provided by the present application, there is also provided a computer program product containing instructions, which, when running on a computer, causes the computer to execute any of the STAR-RIS-assisted secure communication methods for counteracting collaborative eavesdropping in the above embodiments.

[0098] It can be understood that the systems, devices, and storage media provided in the embodiments of the present invention correspond to the methods provided in the embodiments of the present invention. The explanations, examples, and beneficial effects of the relevant content can refer to the corresponding parts in the above methods.

[0099] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (SSD)).

[0100] It should be noted that, in this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including", or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or device that includes a series of elements includes not only those elements but also other elements that are not explicitly listed, or elements that are inherent to such process, method, article, or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article, or device that includes the element.

[0101] Each embodiment in this specification is described in a related manner. The same or similar parts among the embodiments can be referred to each other, and the differences between each embodiment and other embodiments are emphasized. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiment.

[0102] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A STAR-RIS-assisted secure communication method against cooperative multi-eavesdropping, characterized in that: The following steps are included: S1. Initialize the beamforming vectors of each legitimate user and the transmission and reflection coefficients of STAR-RIS; S2, fix the transmission and reflection coefficients, constrain the upper bound of the rate of malicious eavesdropping users, and obtain the beamforming vector by maximizing the rate of legitimate users; S3, fix the beamforming vector, relax the feasible domain of the transflection coefficient, and use the penalty concave-convex process to obtain the solution of the transflection coefficient; S4, repeat S2 and S3, so that the system's safety rate continues to increase until convergence; Step S1 specifically includes: Consider a STAR-RIS-assisted secure communication system consisting of a M A base station with antennas and a N STAR-RIS of 1 unit; There is a legitimate user in the transmission area and reflection area of ​​STAR-RIS. There are several cooperative eavesdroppers around each legitimate user. an eavesdropper; Due to the area separation, eavesdroppers in the two areas cannot cooperate with each other. legitimate users, STAR-RIS to eavesdropper, base station to Legal users, base stations to The channels of the eavesdroppers are , , , , ,in , , and are the set of legitimate users and the set of eavesdroppers respectively. is a plural set; Base station broadcast signal ,in The base station sends k The power normalized signal of each user; for The beamforming vector is limited by the maximum transmit power of the base station. Must meet ;use represents the transmission coefficient matrix and reflection coefficient matrix of STAR-RIS, where , , For the transmission area, is the reflection area; The received signal of each user and The received signals of the eavesdroppers are Formula (1) Formula (2) in is the mapping of the user or eavesdropper to the area where he is located. There are legitimate users in the transmission area of ​​STAR-RIS, then , and Respectively k Users and l The received noise of each eavesdropper follows a complex Gaussian distribution. ; make , , then k The achievable rate of a legitimate user is Formula (3) Located in ξ The eavesdroppers in the area cooperated to eavesdrop on k The achievable rate of a legitimate user is Formula (4) in , For ξ Considering that an eavesdropper in any area can eavesdrop on the signals of two users in the transmission area and the reflection area at the same time, the first k The safe rate for each user is ,in ; Therefore, this security communication system needs to solve the following optimization problems: Formula (5a) Formula (5b) Formula (5c) Formula (5d) Formula (5e) Formula (5f) in .

2. The STAR-RIS-assisted secure communication method against cooperative multi-eavesdropping according to claim 1, characterized in that: Step S2 specifically includes: Perform a first-order Taylor expansion on the rates of legitimate users and eavesdroppers, and at the fixed point Everywhere and The lower and upper bounds of Formula (6) Formula (7) in Formula (8) Formula (9) Formula (10) Formula (11) Formula (12) Formula (13) Formula (14) To take the real part; convert the optimization objective into , at this time the optimization objective is still non-convex, and the auxiliary variable is further introduced and ,have to The upper bound of Formula (15) in Formula (16) Formula (17) Formula (18) at this time It is a quadratic function divided by a linear function, which is a convex function; In order to smooth the objective function, ignore , and transforms the problem of optimizing the beamforming vector into Formula (19a) Formula (19b) Formula (19c) The above problem is a convex problem and is solved using the CVX toolkit.

3. The STAR-RIS-assisted secure communication method against cooperative multi-eavesdropping according to claim 2, characterized in that: Step S3 specifically includes: For the non-convex constraints (5c) and (5d), they are equivalent to ; and the non-convex constraint (5e) is equivalent to Formula (20) Introducing slack variables , relax the feasible domain to Formula (21) Formula (22) Formula (23) Formula (24) The constraint (22) is still non-convex, and further at the fixed point Perform a first-order Taylor expansion on the left side of equation (22), and we get Formula (25) By introducing the penalty term To approximate the original constraint, the subproblem of optimizing the transflection coefficient is transformed into Formula (26a) Formula (26b) After each iteration, optimization Need to update later , that is, The iteration used ,in , and then continue to optimize , until Less than the target accuracy.

4. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the computer program is executed by the processor, the processor is caused to perform the steps of the method according to any one of claims 1 to 3.

5. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the processor is caused to perform the steps of the method according to any one of claims 1 to 3.

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