A method for maximizing secrecy rate of IRS-aided terahertz communication system under HIs

Abstract

The present application relates to a kind of HIs under IRS auxiliary terahertz communication system secret rate maximization method, belong to network security field.Communication system often exists transceiver hardware damage and eavesdropper, which can greatly reduce the security performance of communication system.For this problem, to improve system resource utilization efficiency as target, a kind of HIs under IRS auxiliary terahertz communication system secret rate maximization method is proposed.This method uses alternating optimization, continuous convex approximation, semi-definite programming and other convex optimization methods, considers the HIs of base station and IRS, jointly base station beamforming vector, artificial noise and IRS phase shift, maximizes user secret rate, to obtain optimal security transmission performance, and improve system anti-HIs ability.

Description

Technical Field

[0001] This invention belongs to the field of network security and relates to a method for maximizing the security rate of a terahertz communication system assisted by an Intelligent Reflecting Surface (IRS) under hardware impairments (HIs). Background Technology

[0002] With the commercial rollout of 5G, sixth-generation mobile communication has gradually become a new research hotspot worldwide. Terahertz communication, as a popular 6G technology, boasts advantages such as abundant spectrum resources and strong anti-interference and anti-interception capabilities. However, it still faces some severe technical challenges in practical applications. Terahertz waves suffer from significant path loss and molecular absorption loss, limiting the effective communication distance to a very small range. Furthermore, terahertz beams are narrower and more directional, making them easily blocked by obstacles. IRS technology, with its advantages of low cost, easy deployment, and proactive intelligent control of the wireless propagation environment, can effectively compensate for the shortcomings of terahertz communication. Specifically, IRS uses digital coding to intelligently control electromagnetic waves, forming an electromagnetic field with controllable amplitude, phase, and polarization. This overcomes the uncontrollable characteristics of traditional wireless channels, enabling signal propagation direction control, enhancement, and elimination in three-dimensional space, suppressing interference and enhancing the signal.

[0003] With the development of wireless network transmission, people increasingly rely on wireless networks to transmit important or private information. However, frequent information leaks have made secure wireless communication a critical issue for current and future wireless networks. Physical Layer Security (PLS), as an effective solution for secure wireless communication, has become a hot research topic in the industry. PLS technology utilizes the randomness and variability of channels to weaken the signal reception strength of eavesdroppers (Eves) by introducing artificial noise (AN) or cooperative jammers, thereby achieving secure information transmission. However, these methods require transceivers to perform complex signal processing to adapt the transmitted signal to changes in the wireless environment, which limits the system's secure transmission performance.

[0004] The application of IRS in wireless communication is widely studied. However, research on IRS-assisted terahertz communication systems is relatively limited and focuses primarily on the channel. A search revealed no research on the physical layer security of IRS-assisted terahertz systems under HIS (Hyper-Hyper-Terahertz) conditions. Patent application CN202010162635.7 discloses a design method for a smart reflective surface-assisted terahertz secure communication system, but it does not consider the impact of hardware damage on system security performance in actual communication systems and cannot address situations where transceiver hardware damage leads to low system security performance. Therefore, this paper proposes a method for maximizing the secure rate of IRS-assisted terahertz communication systems under HIS conditions.

[0005] This invention considers the impact of transceiver hijacking (HIs) in practical communication systems. To further ensure user rate fairness, improve system HIs resistance and physical layer security, and design a reasonable resource allocation strategy to maximize system performance, this invention designs an IRS-assisted terahertz communication system transmission optimization scheme. It establishes a multi-input single-output (MISO) single-eavesdropping wireless communication system model for the IRS-assisted terahertz system, aiming to maximize the system's secure rate. Transceiver HIs are considered and modeled as Gaussian distortion noise. Simultaneously, the impact of eavesdroppers on system security is considered, and artificial noise is used to weaken the eavesdropper's signal reception strength. Under the constraints of the base station's maximum transmit power, the user's minimum secure rate, and the IRS phase shift, a joint optimization problem is constructed regarding the beamforming vector, artificial noise, and the IRS phase shift. Summary of the Invention

[0006] In view of this, the purpose of this invention is to provide a method for maximizing the security rate of an IRS-assisted terahertz communication system under HIs.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] A method for maximizing the security rate of an IRS-assisted terahertz communication system under HIS, the method comprising the following steps:

[0009] The system model consists of a base station, an IRS, and K legitimate users with single antennas. Simultaneously, a single-antenna eavesdropper attempts to intercept information transmitted to the legitimate users. The impact of transceiver hardware impairment on system security performance is considered. The model includes the following steps:

[0010] 101. Consider a resource allocation model for maximizing the confidentiality rate of an IRS-assisted terahertz communication system under HIs, construct an optimization problem, and determine whether the constructed problem has a feasible solution;

[0011] 102. After simplifying the original problem through variable substitution, the problem is decomposed into two sub-problems for optimization based on the alternating optimization algorithm. Variable substitution is to introduce auxiliary variables to simplify and replace the original objective function, while adding constraints containing the introduced variables. Specifically, the base station beamforming vector and artificial noise optimization sub-problems are solved by continuous convex approximation and semi-positive definite relaxation, and the IRS phase shift optimization sub-problem is solved by variable substitution and first-order Taylor approximation.

[0012] 103. Solve the convex optimization problem after the equivalent transformation in step 102, solve for the beamforming vector w, artificial noise z and IRS phase shift vector q, obtain the maximum security rate under all constraints, and allocate resources.

[0013] For the downlink of a terahertz communication system, considering the influence of HIs on the base station, the transmitted signal... Represented as:

[0014]

[0015] Where w = w c ;w1;K;w K It is a beamforming vector. Let be the AN vector at the base station, and Z±0 is the covariance matrix of AN. Let This is Gaussian distortion noise caused by the base station HIs. The distortion noise power of each antenna is proportional to its transmitted signal power, and will be expressed as... in, HIs is the transmitter's HIs factor, representing the ratio of transmitted distortion noise power to transmitted signal power.

[0016] Considering the IRS-assisted transmission scheme and the influence of the receiver HIs, the received signal y of user k k It can be represented as

[0017]

[0018] in, The phase matrix represents the IRS reflection model. n represents the reflection phase shift of the m-th unit of the IRS; k It is additive white Gaussian noise at user k, satisfying d k It is Gaussian distortion noise caused by the receiver's HIs, and its distribution is as follows: Let H1 be the HIs factor of the kth legitimate user.

[0019] This paper assumes that the system cannot obtain all the eavesdropper's state information and considers the worst-case scenario: the eavesdropper uses a high-quality eavesdropping device and is unaffected by the receiver HIs, and the eavesdropper receives the signal y.e Represented as

[0020]

[0021] Where, n e It is additive white Gaussian noise at the eavesdropper's location, satisfying...

[0022] The signal-to-noise ratio of the legitimate user k is:

[0023]

[0024] In this denominator, the first term is co-channel interference from other legitimate users, the second term is HIs noise at the base station, the third term is AN interference from the base station, the fourth term is HIs noise interference from legitimate user k, and the fifth term is Gaussian white noise from legitimate user k.

[0025] Similarly, the signal-to-noise ratio of an eavesdropper is expressed as:

[0026]

[0027] Therefore, the transmission rates of the legitimate user k and the eavesdropper are expressed as follows:

[0028] User k successfully decoded the public data stream s c Later from y k Subtract the reconstruction item e from the middle H Y k w c s c Therefore, user k decodes the private data stream s. k The signal-to-interference-plus-noise ratio is expressed as

[0029] R k =log2(1+γ) k )

[0030] R e =log2(1+γ) e )

[0031] To ensure the transmission performance of legitimate users, the security rate for legitimate users must meet the following requirements:

[0032]

[0033] in,

[0034] Under constraints of maximum base station transmit power, minimum user security rate, and IRS phase shift, optimize beamforming vector, artificial noise, and IRS phase shift to maximize system security rate. This optimization problem is expressed as follows:

[0035]

[0036] in, Let C1 be the security rate for user k; constraint C1 is the minimum security rate constraint used to overcome the impact of eavesdroppers on the secure transmission of legitimate user information; C2 is the maximum transmit power constraint at the base station; and C3 is the IRS reflection phase shift constraint.

[0037] Because the optimization variables w, z, and θ in P1 are coupled, and the objective function and constraints are non-convex, this problem is difficult to solve directly. Therefore, this paper adopts the AO method to decouple the optimization variables w, z, and θ in P1, dividing P1 into two convex subproblems for solution.

[0038] First, fix the IRS phase shift vector θ, and optimize the transmitted beamforming vector w and artificial noise z. Let the given θ be... make M k =M H M, N e =N H N, W = ww H At this point, the transmission rates for legitimate users and eavesdroppers can be rewritten as follows:

[0039]

[0040] in

[0041]

[0042] The optimization problem can now be simplified to:

[0043] (P2):

[0044]

[0045] C3:Rank(W k ) = 1

[0046]

[0047] Transform the above problem as follows, let:

[0048]

[0049]

[0050] At this point, the problem remains non-convex, and the optimal solutions for w and z cannot be directly obtained. We use SCA to construct globally underestimated quantities of E1 and E2 to obtain a strictly convex upper bound for the objective function. This is transformed into:

[0051]

[0052] At this point, the non-convex objective function is transformed into the following approximate convex function:

[0053]

[0054] And satisfy

[0055]

[0056] Problem P2 can then be rewritten as problem P3:

[0057] (P3):

[0058]

[0059] C3:Rank(W k ) = 1

[0060]

[0061] However, due to the existence of constraint C3, the problem remains non-convex. By relaxing the rank-1 constraint using SDR, it can be solved using the convex optimization toolbox CVX.

[0062] Given w and z, optimize the phase shift vector q. Introduce auxiliary variables. make Θ=θ H θ, we can obtain:

[0063]

[0064] in

[0065] Approximating (1b) and (2a) using a first-order Taylor series:

[0066]

[0067] At this point, the target problem can be expressed as P4:

[0068] (P4):

[0069]

[0070] (1a),(1c),(1d),(2b),(2c),(2d),(3a),(3c)

[0071] The SDR method is applied to further relax P4 into a convex SPD, and then the CVX toolbox is used to solve the convex problem P4.

[0072] Based on the above two sub-problems, output the optimal beamforming vector w, the optimal IRS phase shift vector q, and the optimal artificial noise z. Update the maximum security rate until convergence, and the solution to the problem is obtained.

[0073] The beneficial effects of this invention are as follows:

[0074] This invention takes into account the situation of transceiver hardware damage and eavesdroppers in real terahertz communication systems, and studies the problem of maximizing the confidentiality rate of IRS-assisted terahertz systems under the condition of hardware damage.

[0075] This invention considers the impact of transceiver hardware damage and eavesdroppers on the security performance of actual communication systems. With the goal of maximizing the secure transmission rate, it considers the transceiver's signal (HIs) and models it as Gaussian distortion noise. Simultaneously, it considers the impact of eavesdroppers on system security by using artificial noise to weaken the eavesdropper's signal reception strength. Under constraints of the base station's maximum transmit power, the user's minimum secure transmission rate, and the IRS phase shift, a joint optimization problem concerning the beamforming vector, artificial noise, and IRS phase shift is constructed. Through auxiliary variable substitution and alternating AO optimization methods, the original non-convex problem is transformed into two convex subproblems, which are then solved. By optimizing the beamforming vector, artificial noise, and IRS phase shift, the maximum secure transmission rate of the system under all constraints is obtained.

[0076] This invention offers advantages over other traditional IRS-assisted terahertz systems, including simpler solutions and lower complexity. It enhances the system's resistance to hardware damage and improves security from a physical layer perspective. Furthermore, it innovatively considers both transceiver hardware damage and the impact of eavesdroppers on system security in real-world communication systems, making the invention more practical and feasible.

[0077] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0078] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein:

[0079] Figure 1 This invention provides a model of an IRS-assisted terahertz communication system under hardware damage conditions.

[0080] Figure 2 This is a flowchart of a method for maximizing the security rate of an IRS-assisted terahertz communication system under a preferred embodiment of the present invention. Detailed Implementation

[0081] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0082] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0083] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "front," and "rear" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0084] Please see Figure 1 The technical solution of the present invention to solve the above-mentioned technical problems is as follows:

[0085] A method for maximizing the security rate of an IRS-assisted terahertz system under hardware impairment conditions. It includes the following steps:

[0086] Step 1: Calculate the feasibility of the problem, and ensure that there is a feasible solution under the problem constraints;

[0087] Step 2: Establish a system model, such as Figure 2 As shown. The system consists of a base station, an IRS, and multiple single-antenna legitimate users. The direct link is blocked by an obstacle. The base station transmits information to the single-antenna legitimate users via cascaded links. Simultaneously, a single-antenna eavesdropper attempts to eavesdrop on the information transmitted to the legitimate users. The IRS includes a set of reflective elements. User set

[0088] Step 3: The channel model from the terahertz base station to the IRS can be represented as:

[0089]

[0090] in, Let f be the composite path gain, d be the center frequency, d be the distance from the terahertz base station to the IRS center point, c be the speed of light, and τ(f) be the medium absorption factor. This represents the channel matrix from the terahertz base station to the IRS. Assuming the channel state information is known, and that both the transmitter and the legitimate user receiver are affected by hardware impairments, we consider the worst-case scenario: that the eavesdropper is unaffected by hardware impairments at the receiver.

[0091] Step 4: The problem of maximizing the security rate of an IRS-assisted terahertz system under hardware impairment conditions is expressed as follows:

[0092] (P1):

[0093]

[0094]

[0095]

[0096] in, Let C1 be the security rate for user k; constraint C1 is the minimum security rate constraint used to overcome the impact of eavesdroppers on the secure transmission of legitimate user information; C2 is the maximum transmit power constraint at the base station; and C3 is the IRS reflection phase shift constraint.

[0097] Step 5: Fix the IRS phase shift θ, optimize the beamforming vector w and artificial noise z, and reformulate P1 as P2, i.e.

[0098] (P2):

[0099]

[0100] C3:Rank(W k ) = 1

[0101]

[0102] Using SCA to construct globally underestimated quantities of E1 and E2, we obtain a strictly convex upper bound for the objective function. At this point, the non-convex objective function is transformed into an approximately convex function, and problem P2 is transformed into P3:

[0103] (P3):

[0104]

[0105] C3:Rank(W k ) = 1

[0106]

[0107] Step 6: Optimize the IRS phase shift q while fixing the beamforming vector w and artificial noise z. Problem P1 becomes P4:

[0108] (P4):

[0109]

[0110] (1a),(1c),(1d),(2b),(2c),(2d),(3a),(3c)

[0111] Step 7: For the maximum security rate The update process involves the following steps: Based on the two sub-problems, output the optimal beamforming vector w, the optimal IRS phase shift vector q, and the optimal artificial noise z. Update the maximum security rate until convergence, at which point the solution to the problem is obtained.

[0112] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for maximizing the secure rate of an IRS-assisted terahertz communication system under HIS, wherein the system consists of a base station, an IRS, and multiple single-antenna legitimate users, wherein, The direct link is blocked by an obstacle. The base station transmits information to a legitimate user with a single antenna via a cascaded link. Simultaneously, a single-antenna eavesdropper attempts to eavesdrop on the information transmitted to the legitimate user. The system considers Hierarchical Intrusion (HIs), and there are corresponding hardware impairment noises at both the base station and the IRS. The IRS reflects the noise. User set The method is characterized by the following steps:

101. Initialize the base station's maximum transmit power, artificial noise power, HIs coefficients of the transmitter and receiver, and the number of users. Establish a mathematical model for the original optimization problem of the security rate and find that the original optimization problem is a non-convex problem.

102. After simplifying the original problem by variable substitution, the problem is decomposed into two sub-problems for optimization based on the alternating optimization algorithm. Variable substitution is to introduce auxiliary variables to simplify and replace the original objective function, while adding constraints containing the introduced variables. The base station beamforming vector and artificial noise optimization sub-problems are solved by continuous convex approximation and semi-positive definite relaxation, and the IRS phase shift optimization sub-problem is solved by variable substitution and first-order Taylor approximation.

103. Solve the convex optimization problem after the equivalent transformation in step 102, and solve for the beamforming vector w, artificial noise z and IRS phase shift vector θ, and obtain the maximum security rate based on all constraints. The channel state information of the system is known, and the channel gains of BS-IRS, IRS-user k, and IRS-eavesdropper are expressed as follows: For the downlink of a terahertz communication system, considering the influence of HIs on the base station, the transmitted signal... Represented as Where w = w c ;w1;K;w K It is a beamforming vector. Let be the vector of artificial noise (AN) at the base station, and Let AN be the covariance matrix; let This is Gaussian distortion noise caused by the base station HIs. The distortion noise power of each antenna is proportional to its transmitted signal power, and will be expressed as... in, The HIs factor at the transmitting end represents the ratio of transmitted distortion noise power to transmitted signal power; A mathematical model is established for maximizing the security rate of the system, and the objective function is: in, Let C1 be the security rate for user k; constraint C1 is the minimum security rate constraint, used to overcome the impact of eavesdroppers on the secure transmission of legitimate user information; C2 is the maximum transmit power constraint at the base station; and C3 is the IRS reflection phase shift constraint. The P1 is solved using the AO method, and the solution steps are as follows: fix θ, optimize the beamforming vector w and artificial noise z; fix w and z, optimize the IRS phase shift vector θ; repeat the process alternately until... The solution to the problem converges and is obtained. The optimized beamforming vector w and artificial noise z are specifically as follows: With a fixed phase shift vector θ, let the given θ be... M k =M H M, N e =N H N, W = ww H ,make At this point, the transmission rates for legitimate users and eavesdroppers are rewritten as follows: The optimization problem then simplifies to: C3:Rank(W k )=1 Transform the above problem as follows, let: At this point, the problem is still non-convex, and the optimal solutions for w and z cannot be directly obtained; SCA is used to construct globally underestimated quantities of E1 and E2 to obtain a strictly convex upper bound for the objective function; it is then transformed into: At this point, the non-convex objective function is transformed into the following approximate convex function: And satisfy Problem P2 can then be rewritten as Problem P3: C3:Rank(W k )=1 Given constraint C3, the problem is non-convex; by relaxing the constraint with rank 1 using SDR, it can be solved using the convex optimization toolbox CVX. The phase shift vector θ is optimized as follows: Given w and z, introduce auxiliary variables. make Θ=θ H θ, we get: in Approximating (1b) and (2a) using a first-order Taylor series: At this point, the target problem is expressed as P4: (1a),(1c),(1d),(2b),(2c),(2d),(3a),(3c) The SDR method is applied to further relax P4 into a convex SPD, and then the CVX toolbox is used to solve the convex problem P4. Based on P3 and P4, output the optimal beamforming vector w, the optimal IRS phase shift vector θ, and the optimal artificial noise z. Update the maximum security rate until convergence, and the solution to the problem is obtained.

Images