Method for guaranteeing non-ground network communication security
By constructing a primary network and secondary networks, optimizing UAV transmission power and the BD-RIS phase shift matrix, the vulnerability of non-terrestrial networks to attacks was solved, achieving maximum confidentiality and network security under interference constraints.
Patent Information
- Application Number
- CN202511196389.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-26
- Publication Date
- 2025-11-18
AI Technical Summary
Non-terrestrial networks are vulnerable to eavesdropping and malicious attacks, and existing technologies struggle to meet security requirements while simultaneously integrating different types of networks.
A primary network and a secondary network are constructed. A high-altitude platform station and a UAV carrying a diagonally reconfigurable smart surface are used. By calculating the signal-to-interference-plus-noise ratio, the transmission power of the UAV and the phase shift matrix of BD-RIS are optimized to maximize the security rate of the secondary network. An alternating optimization method and Steifel manifold are used to optimize the phase shift matrix.
While meeting interference limits, it maximizes the confidentiality rate, effectively balances power allocation and BD-RIS phase shift optimization, and ensures network security.
Smart Images
Figure CN120980518A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of network communication security technology, specifically a method for ensuring the security of non-terrestrial network communications. Background Technology
[0002] The convergence of terrestrial and non-terrestrial (T-NT) communication networks is a new trend in the development of future 6G communication technology. This strategy enhances remote communication and processing capabilities by incorporating air and space platforms, such as high-altitude platforms or satellite platforms, providing infrastructure for the connection of nodes in remote areas. In non-terrestrial networks, low Earth orbit satellites form a dense network of interconnected nodes around the Earth.
[0003] The open nature of wireless communication makes non-terrestrial networks vulnerable to eavesdropping and other malicious attacks. Therefore, it is necessary to seek solutions that can meet security requirements while also accommodating the integration of different types of networks coexisting in the same spectrum. Summary of the Invention
[0004] To address the shortcomings of existing technologies, this invention provides a method for ensuring the security of non-terrestrial network communications, thus solving the problems mentioned in the background section.
[0005] To achieve the above objectives, the present invention provides a method for ensuring the security of non-terrestrial network communications, comprising the following steps:
[0006] S1. Construct a communication system:
[0007] The communication system includes a main network and a secondary network. The main network includes a high-altitude platform station as the main transmitter, which is used to transmit signals to the main users. The secondary network includes a drone equipped with a diagonally reconfigurable smart surface, which is used as a secondary transmitter to transmit signals to secondary user devices. Malicious users exist in the secondary network.
[0008] S2. Calculate the signal-to-interference-plus-noise ratio for secondary users and malicious users:
[0009] The channel vector h from the secondary transmitter to the secondary user s The channel vector h from the secondary transmitter to the malicious user e h s and h e The transmission follows Ricean attenuation; calculate the signal-to-interference-plus-noise ratio for secondary users and malicious users.
[0010] S3. Determine the secondary network security rate:
[0011] The secondary network security rate is defined as:
[0012] R sec=max(0,R) s -R e )
[0013] Among them, R s =log(1+γ) s ),R e =log(1+γ) e )
[0014] To ensure the quality of service of the primary network, the interference power caused by secondary users to primary users is subject to the interference temperature limit I. th The constraint is that g is a constant:
[0015] |gΦ| 2 P s ≤I th ;
[0016] S4. Maximize the secondary network security rate:
[0017] Maximize the security rate of the secondary network by optimizing the drone's transmit power and the phase shift matrix of BD-RIS.
[0018] Furthermore, in step S1, the transverse reconfigurable smart surface is abbreviated as BD-RIS. BD-RIS consists of M reconfigurable units, and the main network and the secondary network share the same spectrum.
[0019] Furthermore, in step S2, h s In this context, s stands for second, which is an M-dimensional vector.
[0020] h e In this context, 'e' stands for evil, representing a malicious user, and is also an M-dimensional vector.
[0021] Furthermore, in step S2, the specific process for calculating the signal-to-interference-plus-noise ratio for secondary users and malicious users is as follows:
[0022] The signals received by secondary users and malicious users from the secondary transmitter are defined as follows:
[0023]
[0024] x is the signal transmitted from the secondary transmitter to the secondary user, z is the signal transmitted from the primary transmitter to the primary user, and Φ is the phase shift matrix of BD-RIS with dimension (M). x M y ), satisfying constraint ΦΦ H =I M I is the identity matrix, n s and n e It is noise that follows a Gaussian distribution, with an expected value of 0 and a variance of . and P s The transmission power of this transmitter, Q p It is the transmission power of the main transmitter;
[0025] The signal-to-interference-plus-noise ratios (SINR) for secondary users and malicious users are respectively:
[0026]
[0027] Furthermore, in step S4, the optimization problem of maximizing the confidentiality rate is expressed as:
[0028] Question P:
[0029] Constraints:
[0030] |gΦ| 2 P s ≤I th
[0031] 0≤P s ≤P max
[0032] ΦΦ H =I M
[0033] in[·] + The result must be a positive number, which is equivalent to max{0,(·)}.
[0034] Furthermore, due to P s Given the coupling relationship with Φ, problem P is non-convex. Therefore, the alternating optimization method is used to effectively solve it, decomposing problem P into two subproblems and optimizing the transmit power P of the subnetwork. s And two, the phase shift matrix Φ of BD-RIS.
[0035] Furthermore, regarding the issue of transmission power:
[0036] If the phase shift matrix Φ of BD-RIS is fixed, then problem P is simplified to:
[0037] Subproblem P1:
[0038] Constraints:
[0039] |gΦ| 2 P s ≤I th Constraint 1
[0040] 0≤P s ≤P max Constraint 2
[0041] In subproblem P1, the objective function is [log(1+γ] s )-log(1+γ e )] + via γ s and γ e With P s Monotonically increasing, in this case, the optimal power P s The optimal power is determined by the disturbance constraint in constraint 1 and the maximum power constraint in constraint 2. Represented as:
[0042]
[0043] However, if it is:
[0044]
[0045] Then log(1+γ) e The result will be greater than or equal to log(1+γ). s This causes the security rate to become 0. In this case, the optimal transmission power is 0. Considering the above factors, Expressed as:
[0046]
[0047] Furthermore, regarding the design problem of the phase shift matrix:
[0048] If the transmission power P of the secondary network s If it is fixed, then problem P simplifies to a phase shift matrix design problem:
[0049] Subproblem P2:
[0050] Constraints:
[0051] |gΦ| 2 P s ≤I th
[0052] ΦΦ H =I M
[0053] Since the objective function involves the difference between two logarithmic functions, and γ s and γ e It is a quadratic function of Φ, which makes the objective function nonlinear and nonconvex. Therefore, we use the Steifel manifold to solve this problem. Φ is regarded as a point on the Steifel manifold, where the Steifel manifold is all (M,M)-dimensional unitary matrices.
[0054] Introducing the Lagrange multiplier λ and defining the augmented Lagrange function as:
[0055]
[0056] Obtain the objective function The Euclidean gradient with respect to Φ is described as:
[0057]
[0058] Where A s =h s Φ,A e =h e The Euclidean gradient Φ provides the direction of steepest ascent in the surrounding space, which is then projected onto the tangent space of the Stiefel manifold. The Euclidean gradient is then projected onto the Stiefel manifold at the current point Φ. k On the tangent space:
[0059]
[0060] k represents the iteration number. If a constraint is violated during the iteration, the step size I is adjusted. th Update the projection back to the feasible area:
[0061]
[0062] The tangent space is a manifold in Φ k The linear approximation at the point ensures that the gradient direction follows the geometry of the manifold. This connects the Euclidean gradient to the manifold structure, thus ensuring that the update remains consistent with the constraints. The matrix exponential method is used to update Φ on the manifold:
[0063]
[0064] This method is used to iteratively update Φ, continuously optimizing the phase shift matrix until convergence.
[0065] Furthermore, the step size η k Control the movement along the geodesic path of the manifold to ensure that the optimization process is stable and efficient. Repeat the iterative process of formulas 1-5 until convergence to the optimal phase shift matrix.
[0066] This invention provides a method for ensuring the security of non-terrestrial network communications, which has the following beneficial effects:
[0067] 1. This method for ensuring the security of non-terrestrial network communications can maximize the confidentiality rate while meeting interference restrictions. It can effectively balance power allocation and BD-RIS phase shift optimization. Based on the characteristics of the problem, an alternating optimization method is proposed. It uses a low-complexity power allocation strategy and Stifel manifold optimization for phase adjustment to achieve iterative convergence of the optimization solution. Attached Figure Description
[0068] Figure 1 This is a schematic diagram of the system structure of a method for ensuring the security of non-terrestrial network communications according to the present invention;
[0069] Figure 2 This is a flowchart illustrating the steps of a method for ensuring the security of non-terrestrial network communications according to the present invention. Detailed Implementation
[0070] The embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and should not be construed as limiting the scope of the invention.
[0071] like Figures 1-2 As shown, the present invention provides a technical solution: a method for ensuring the security of non-terrestrial network communications, comprising the following steps:
[0072] S1. Construct a communication system:
[0073] The communication system includes a main network and a secondary network. The main network includes an aerial platform station as the main transmitter, used to transmit signals to the main users. The secondary network includes a drone carrying a diagonal reconfigurable smart surface, which serves as a secondary transmitter to transmit signals to secondary user devices. Malicious users may exist in the secondary network. The diagonal reconfigurable smart surface is abbreviated as BD-RIS. BD-RIS consists of M reconfigurable units. The main network and the secondary network share the same spectrum.
[0074] S2. Calculate the signal-to-interference-plus-noise ratio for secondary users and malicious users:
[0075] The channel vector h from the secondary transmitter to the secondary user s The channel vector h from the secondary transmitter to the malicious user e h s and h e The transmission follows Ricean attenuation, h s In this context, s stands for second, which is an M-dimensional vector.
[0076] h e In this context, 'e' stands for evil, representing a malicious user, and is also an M-dimensional vector.
[0077] The specific process for calculating the signal-to-interference-plus-noise ratio for secondary users and malicious users is as follows:
[0078] The signals received by secondary users and malicious users from the secondary transmitter are defined as follows:
[0079]
[0080]
[0081] x is the signal transmitted from the secondary transmitter to the secondary user, z is the signal transmitted from the primary transmitter to the primary user, and Φ is the phase shift matrix of BD-RIS with dimension (M). x M y ), satisfying constraint ΦΦ H =I M I is the identity matrix, n s and n e It is noise that follows a Gaussian distribution, with an expected value of 0 and a variance of . and P s The transmission power of this transmitter, Q p It is the transmission power of the main transmitter;
[0082] The signal-to-interference-plus-noise ratios (SINR) for secondary users and malicious users are respectively:
[0083]
[0084] S3. Determine the secondary network security rate:
[0085] The security rate, also known as the security ratio, is a metric defined as the difference between the achievable data rates of a legitimate channel and an eavesdropping channel.
[0086] The secondary network security rate is defined as:
[0087] R sec =max(0,R) s -R e )
[0088] Among them, R s =log(1+γ) s ),R e =log(1+γ) e )
[0089] To ensure the quality of service of the primary network, the interference power caused by secondary users to primary users is subject to the interference temperature limit I. th The constraint is that g is a constant:
[0090] |gΦ| 2 P s ≤I th;
[0091] Interference temperature: When licensed users and unlicensed users share the same spectrum, the normal operation of licensed users must be ensured first. The system needs to estimate the interference value that the licensed system can accept in advance, predict the interference that will be brought to the licensed user's receiver after the introduction of unlicensed users, and determine whether to allow the addition of unlicensed users in this way.
[0092] S4. Maximize the secondary network security rate:
[0093] Maximize the security rate of the secondary network by optimizing the drone's transmit power and the phase shift matrix of BD-RIS;
[0094] The optimization problem of maximizing confidentiality is expressed as:
[0095] Question P:
[0096] Constraints:
[0097] |gΦ| 2 P s ≤I th
[0098] 0≤P s ≤P max
[0099] ΦΦ H =I M
[0100] in[·] + The result must be a positive number, equivalent to max{0,(·)}, where · is log(1+γ). s )-log(1+γ e );
[0101] Because of P s Given the coupling relationship with Φ, problem P is non-convex. Therefore, the alternating optimization method is used to effectively solve it, decomposing problem P into two subproblems and optimizing the transmit power P of the subnetwork. s And two, the phase shift matrix Φ of BD-RIS;
[0102] Regarding the issue of transmission power:
[0103] If the phase shift matrix Φ of BD-RIS is fixed, then problem P is simplified to:
[0104] Subproblem P1:
[0105] Constraints:
[0106] |gΦ| 2 Ps ≤I th Constraint 1
[0107] 0≤P s ≤P max Constraint 2
[0108] In subproblem P1, the objective function is [log(1+γ] s )-log(1+γ e )] + via γ s and γ e With P s Monotonically increasing, in this case, the optimal power P s The optimal power is determined by the disturbance constraint in constraint 1 and the maximum power constraint in constraint 2. Represented as:
[0109]
[0110] However, if it is:
[0111]
[0112] Then log(1+γ) e ) will be greater than or equal to log(1+γ) s This causes the security rate to become 0. In this case, the optimal transmission power is 0. Considering the above factors, Expressed as:
[0113]
[0114] The design problem of phase shift matrix:
[0115] If the transmission power P of the secondary network s If it is fixed, then problem P simplifies to a phase shift matrix design problem:
[0116] Subproblem P2:
[0117] Constraints:
[0118] |gΦ| 2 P s ≤I th
[0119] ΦΦ H =I M
[0120] Since the objective function involves the difference between two logarithmic functions, and γ s and γ eIt is a quadratic function of Φ, making the objective function nonlinear and nonconvex. Therefore, the Steifel manifold is used to solve this problem. Φ is regarded as a point on the Steifel manifold, where the Steifel manifold is all (M,M)-dimensional unitary matrices. The Steifel manifold is composed of all orthogonal k-dimensional frames in Euclidean space. It can be understood that the Steifel manifold is the set of all orthogonal matrices.
[0121] Introducing the Lagrange multiplier λ and defining the augmented Lagrange function as:
[0122]
[0123] Obtain the objective function The Euclidean gradient with respect to Φ is described as:
[0124]
[0125] Where A s =h s Φ,A e =h e The Euclidean gradient Φ provides the direction of steepest ascent in the surrounding space, which is then projected onto the tangent space of the Stiefel manifold. The Euclidean gradient is then projected onto the Stiefel manifold at the current point Φ. k On the tangent space:
[0126]
[0127] k represents the iteration number. If a constraint is violated during the iteration, the step size I is adjusted. th Update the projection back to the feasible area:
[0128]
[0129] The tangent space is a manifold in Φ k The linear approximation at the point ensures that the gradient direction follows the geometry of the manifold. This connects the Euclidean gradient to the manifold structure, thus ensuring that the update remains consistent with the constraints. The matrix exponential method is used to update Φ on the manifold:
[0130]
[0131] This method is used to iteratively update Φ, continuously optimizing the phase shift matrix until convergence, with a step size η. k Control the movement along the geodesic path of the manifold to ensure that the optimization process is stable and efficient. Repeat the iterative process of formulas 1-5 until convergence to the optimal phase shift matrix.
[0132] Based on the above description, this invention can maximize the security rate while satisfying interference constraints, effectively balance power allocation and BD-RIS phase shift optimization, and propose an alternating optimization method based on the characteristics of the problem. It utilizes a low-complexity power allocation strategy and Stifel manifold optimization for phase adjustment to achieve iterative convergence of the optimization solution.
[0133] The embodiments of the present invention are given for illustrative and descriptive purposes only, and are not intended to be exhaustive or to limit the invention to the forms disclosed. Many modifications and variations will be apparent to those skilled in the art. The embodiments were chosen and described in order to better illustrate the principles and practical application of the invention, and to enable those skilled in the art to understand the invention and to design various embodiments with various modifications suitable for a particular purpose.
Claims
1. A method for ensuring the security of non-terrestrial network communications, characterized in that: The method comprises the following steps: S1, constructing a communication system: The communication system comprises a primary network and a secondary network, the primary network comprises a high-altitude platform station as a primary transmitter for transmitting signals for primary users, the secondary network comprises a drone carrying a beyond diagonal reconfigurable intelligent surface as a secondary transmitter for transmitting signals for secondary user equipment, and there is a malicious user in the secondary network; S2, calculating the signal-to-interference-plus-noise ratio of the secondary user and the malicious user: Channel vector h from the secondary transmitter to the secondary user s Channel vector h from the secondary transmitter to the malicious user e Transmission of h s and h e is subject to Rician fading, compute the signal-to-interference-plus-noise ratio of the secondary user to the malicious user; S3, determining the secondary network secrecy rate: The secondary network secrecy rate is defined as: R sec = max(0, R s - R e ) where R s = log(l + γ s ), R e = log(l + γ e ) To ensure the quality of service of the primary network, the interference power caused by the secondary users to the primary users is constrained by an interference temperature limit I th , g being a constant: |gΦ| 2 P s ≤I th ; S4, maximizing the secondary network secrecy rate: The transmission power of the drone and the phase shift matrix of the BD-RIS are optimized to maximize the secrecy rate of the secondary network.
2. The method of claim 1, wherein the method further comprises: In the step S1, the beyond diagonal reconfigurable intelligent surface is referred to as BD-RIS, the BD-RIS is composed of M reconfigurable units, and the primary network and the secondary network share the same frequency spectrum.
3. The method of claim 1, wherein the method further comprises: In the step S2, h s s is second, representing secondary, and is an M-dimensional vector. h e e is evil, representing a malicious user, and is also a vector of dimension M.
4. The method of claim 1, wherein the method further comprises: In the step S2, the process of calculating the signal-to-interference-plus-noise ratio of the secondary user and the malicious user is as follows: The signals received by the secondary user and the malicious user from the secondary transmitting end are defined as: x is the signal transmitted from the secondary transmitter to the secondary user, z is the signal transmitted from the primary transmitter to the primary user, Φ is the phase shift matrix of the BD-RIS, with dimension (M x ,M y ), satisfying the constraint ΦΦ H = I M , I is the identity matrix, n s and n e are noises satisfying Gaussian distribution, with expectation 0 and variance and P s is the transmission power of the secondary transmitter, Q p is the transmission power of the primary transmitter; The signal-to-interference-plus-noise ratios of the secondary user and the malicious user are respectively:
5. The method of claim 1, wherein: In the step S4, the optimization problem of maximizing the secrecy rate is expressed as: Problem P: Constraint condition: |gΦ| 2 P s ≤I th 0 < P s ≤ P max ΦΦ H = I M where [·] + denotes the result needs to be a positive number, equivalent to max{0, (·)}.
6. The method of claim 5, wherein the method further comprises: Due to the coupling relationship between P s and Φ, the problem P is non-convex, so it is effective to solve it using the alternating optimization method subsequently, which decomposes the problem P into two sub-problems, optimizing the transmit power P s of the secondary network and the phase shift matrix Φ of the BD-RIS respectively.
7. The method of claim 6, wherein the method further comprises: For the transmission power problem: If the phase shift matrix Φ of the BD-RIS is fixed, the problem P is simplified as: Sub-problem P1: Constraint condition: |gΦ| 2 P s ≤I th Constraint 1 0 < P s ≤ P max Constraint 2 In sub-problem P1, the objective function [log(1+γ s )-log(1+γ e )] + By γ s and γ e monotonically increasing with P s , in this case, the optimal power P s is determined by the interference constraint in constraint 1 and the maximum power constraint in constraint 2, the optimal power is expressed as: But if: So log(1 + γ e ) will be greater than or equal to log(1 + γ s ), resulting in the secrecy rate becoming 0, in which case the optimal transmission power is 0, and in combination with the above cases, is expressed as:
8. The method of claim 7, wherein the method further comprises: receiving a request for a connection from a non-terrestrial network device; and determining whether the non-terrestrial network device is authorized to connect to the network based on the received information. For the design problem of the phase shift matrix: If the transmit power P s of the secondary network is fixed, then the problem P simplifies to a phase shift matrix design problem: Sub-problem P2: Constraint condition: |gΦ| 2 P s ≤I th ΦΦ H = I M Since the objective function involves the difference of two logarithmic functions, and γ s and γ e are quadratic functions of Φ, such that the objective function is non-linear and non-convex, the Steiner manifold is employed to solve this problem, Φ is considered as a point on the Steiner manifold, where the Steiner manifold is the set of all (M, M) -dimensional unitary matrices; The Lagrange multiplier λ is introduced and the augmented Lagrange function is defined as: The objective function is obtained The Euclidean gradient with respect to Φ is described as: where A s = h s Φ, A e = h e The Euclidean gradient provides the direction of steepest ascent in the ambient space, which is then projected onto the tangent space of the Stiefel manifold. The Euclidean gradient is projected onto the tangent space of the Stiefel manifold at the current point Φ k : k represents the iteration number, if there is a violation of the constraints in the iteration, the step size I is adjusted th , update the projection back to the feasible region: The tangent space is the linear approximation of the manifold at Φ k at Φ, the projection ensures that the gradient direction follows the geometry of the manifold, which is able to connect the Euclidean gradient with the manifold structure, thus ensuring that the update is consistent with the constraints, using the matrix exponential method to update Φ on the manifold: The phase shift matrix Φ is updated iteratively by this method, and the phase shift matrix is continuously optimized until convergence.
9. The method of claim 8, wherein the method further comprises: Step size η k Controlling the movement along the geodesic path of the manifold ensures that the optimization process is stable and efficient, and the process of iterating Equations 1-5 is repeated until convergence to the optimal phase shift matrix is achieved.