A method for RIS-assisted satellite-ground secure communication in the presence of interference

Abstract

This invention discloses a RIS-assisted secure satellite-to-ground communication method under interference, belonging to the field of secure satellite-to-ground communication. The invention is used in a RIS-assisted secure satellite-to-ground communication system, including a satellite transmitter, a RIS, a UAV, a receiver, and multiple EVEs. The UAV is used to transmit harmful interference signals. With maximizing the secure rate as the objective, and constrained by satellite transmit power constraint CR1 and RIS constant modulus constraint CR2, a secure communication system optimization problem is constructed. By using maximizing the secure rate as the optimization objective, secure communication is ensured even with the worst-case receiver. The satellite transmit power constraint CR1 ensures effective transmission by the signal transmitter, and the RIS constant modulus constraint CR2 ensures signal reflection. The RIS constant modulus constraint CR2 and the objective function are deconvexized, and the deconvexized secure communication system optimization problem is jointly optimized to obtain the maximized secure rate, ensuring reliable and secure communication of the multi-user secure communication system even under noise uncertainty.

Description

Technical Field

[0001] This invention relates to a RIS-assisted secure satellite-to-ground communication method under interference, belonging to the field of secure satellite-to-ground communication. Background Technology

[0002] In recent years, the rapid development of high-speed communication technology has significantly advanced the development of space-to-ground communication systems. These systems have enabled seamless data transmission and information exchange between spacecraft and ground stations. However, with the widespread application of space-to-ground communication in civilian, military, and commercial activities, the sensitive data transmitted by these systems also faces threats from cyberattacks and other malicious activities, making it crucial to ensure the security of space-to-ground communication systems. Existing methods such as encryption, authentication, artificial intelligence, and physical security measures each have their advantages and disadvantages. For example, encryption may introduce latency and is vulnerable to decryption attacks, authentication may be forged, and physical security measures, while effective, still have risks of evasion. Reconfigurable smart surface (RIS) technology, as a cutting-edge technology in recent years, can dynamically adjust its surface structure to control electromagnetic wave propagation, effectively eliminating signal obstacles and multipath interference, and improving signal quality and coverage. Active RIS has the ability to precisely control signal amplitude, phase, and direction. Although it is more expensive and consumes more energy, it has significant advantages over traditional antenna systems. Passive RIS, while having lower cost and energy consumption, is slightly less accurate. Existing research mainly focuses on the application of UAVs as receivers or relays, while this study innovatively proposes to use UAVs as a source of interference to explore the impact of UAV interference on system performance, thus expanding our understanding of UAV capabilities and their potential impact on RIS-assisted communication systems. Summary of the Invention

[0003] To address the following technical shortcomings of existing MIMO covert communication methods: (i) the problems of constructing multiple eavesdropping networks and multi-user collaborative optimization under resource constraints; and (ii) the low secure transmission rate and poor resource utilization in traditional RIS-based satellite-to-ground secure communication systems, the main objective of this invention is to provide a RIS-assisted satellite-to-ground secure communication method under UAV interference. Leveraging the unique performance of RIS in controlling reflected signals, a RIS module is added to a multi-user covert communication system consisting of a satellite transmitter, multiple receiver eavesdroppers (EVEs), and one or more user receivers. The goal is to maximize the secure transmission rate, with constraints including the RIS constant modulus constraint CR2 and the Alice transmit power constraint CR1. An optimization problem for the secure communication system is constructed, and the secure and efficient transmission of the satellite-to-ground communication system is achieved based on the optimization results of this problem.

[0004] The objective of this invention is achieved through the following technical solution.

[0005] This invention discloses a RIS-assisted satellite-to-ground secure communication method under interference, comprising the following steps:

[0006] Step 1: The secure communication system includes a satellite transmitter, a RIS (Radio Recognition System), a UAV (Unmanned Aerial Vehicle), a receiver, and multiple EVEs (External Virtual Machines). The UAV is used to transmit harmful interference signals and construct the secure communication system model. The RIS is used to reflect signals; the user and the EVEs jointly receive signals transmitted by Alice and reflected by the RIS; Willie detects whether Alice is transmitting a useful signal. The secure communication system model includes channel models for the satellite-to-ground communication system, satellite-to-user channel models, satellite-to-EVE channel models, satellite-to-user and EVE channel models, and UAV-to-user channel models.

[0007] Considering rain attenuation and free path loss, the channel model of the satellite-to-ground communication system is expressed as follows:

[0008]

[0009] The satellite-to-user channel model for a RIS-based secure space-to-ground communication system is represented as follows:

[0010]

[0011] The satellite-to-EVE channel model of a RIS-based space-to-ground secure communication system is represented as follows:

[0012]

[0013] In a non-ideal scenario, the channel model for a RIS-based satellite-to-user and EVE communication system is expressed as follows:

[0014]

[0015] The UAV-to-user channel model of a RIS-based space-to-ground secure communication system is represented as follows:

[0016]

[0017] Where: C L λ represents the free space loss. s Let N be the carrier wavelength of the satellite ground channel, ξ be the rain attenuation power loss, f be the overall satellite channel ξ rain attenuation, Φ[n] be the phase matrix of RIS, and N be the total number of satellites. R h represents the number of RIS units. SU For direct transmission from satellite users, H SR To access the satellite RIS channel, h RU For direct connection from the user channel, For the i-th EVE channel from the satellite, For the channel from RIS to the i-th EVE, h u For the overall channel from satellite to user, For the ideal channel from satellite to user, Δh u For the channel error from satellite to user, The total channel from the satellite to the i-th EVE, For the ideal channel from the satellite to the i-th EVE, H represents the channel error from the satellite to the i-th EVE. VR For the channel interference from drones to users, h v For the channel between the drone and the RIS.

[0018] Step 2: The satellite transmitter transmits signals via wireless communication, modulating the baseband signal onto the carrier signal; the power of the satellite transmitter satisfies constraint CR1, whereby the total power of the satellite transmitter at the current moment is less than a fixed constraint power.

[0019] The transmitted signal s is represented as

[0020] s[n]=w[n](x[n]+n s [n])

[0021] Where: the signal is represented by x, and w is the beamforming data that meets the transmit power constraint requirements.

[0022] Step 3: The user receiver simultaneously receives signals transmitted by the satellite transmitter, interference signals transmitted by the UAV, and signals reflected by the RIS.

[0023] The signal received by the receiver is represented as

[0024] y U [n] = h u s[n]+h ν s in [n]+z l [n]

[0025] in: This is the noise received by the EVE.

[0026] Step 4: The EVE receiver receives signals transmitted by the satellite and signals reflected by the RIS;

[0027] The signal received by the i-th EVE is represented as shown in formula (3);

[0028]

[0029] in: This is the noise received by the user.

[0030] Step 5: For the RIS-assisted secure communication system, with the goal of maximizing the secure rate, and constraints including satellite transmit power constraint CR1 and RIS constant mode constraint CR2, an optimization problem for the secure communication system is constructed. By using the maximization of the secure rate as the optimization objective, secure communication can be achieved even by the worst receiver in both single-user and multi-user communication systems, thereby enabling each receiver user to achieve secure reception while ensuring secure communication. The effective transmission of the signal transmitter is ensured by the satellite transmit power constraint CR1, and the signal reflection is ensured by the RIS constant mode constraint CR2.

[0031] The objective function for the optimization problem of a secure communication system is as follows:

[0032]

[0033]

[0034]

[0035] max R s

[0036] w[n],Φ[n]

[0037] st||w[n]|| 2 ≤P u

[0038]

[0039] Where: CR1 is the satellite's maximum transmit power constraint, P u R1 represents the maximum transmit power of the transmitter; R2 represents the RIS amplitude constant mode constraint.

[0040] Step Six: According to Jensen's inequality, when considering the constraints, both the RIS constant modulus constraint CR2 and the objective function are non-convex problems that are difficult to solve directly. For single-user passive RIS secure communication systems, single-user active RIS secure communication systems, and multi-user non-ideal secure communication systems, non-convexification methods are constructed to non-convexize the RIS constant modulus constraint CR2 and the objective function, respectively, resulting in the non-convexized secure communication system optimization problem. By jointly optimizing the non-convexized secure communication system optimization problem, the maximum secure rate of the secure communication system is obtained, ensuring that the multi-user secure communication system can still communicate reliably and securely under noise uncertainty.

[0041] ① For a single-user passive RIS secure communication system, an iterative optimization algorithm is used to optimize the precoding parameter w and the RIS phase parameter.

[0042] Step ①.1: Optimize the precoding parameter w by fixing the RIS phase parameters and using the LogSumExp function to transform the objective function of the secure communication system optimization problem into...

[0043]

[0044] The KKT method is used to find the optimal solution for the precoding parameter w, thereby obtaining the maximum secure rate.

[0045] Using the precoding parameters w obtained in step ①.2 and step ①.1, construct the optimal base station transmit beamformer and fix the receive beamformer. Use the projection gradient ascent method to handle the RIS constant mode constraint CR2 problem and solve for the optimal RIS phase parameters.

[0046] Step ①.3: Based on steps ①.1 and ①.2, iterate repeatedly on the secure communication system optimization problem, jointly optimizing the base station transmit beamformer and the RIS reflection matrix; determine whether the result is less than the convergence accuracy threshold, or whether the maximum number of iterations has been reached. If so, end the iteration, output the jointly optimized base station transmit beamformer and RIS reflection signal matrix, thus obtaining the optimal base station transmit beam and RIS reflection parameters, maximizing the secure rate. Otherwise, continue the iteration.

[0047] ② For a single-user active RIS secure communication system, an iterative optimization algorithm is used to optimize the precoding parameter w and the RIS phase and amplitude parameters.

[0048] Step ②.1: Optimize the precoding parameter w by fixing the RIS phase parameters and using the LogSumExp function to define the objective function of the secure communication system optimization problem as follows:

[0049]

[0050] The KKT method is used to find the optimal solution for the precoding parameter w, thereby obtaining the maximum secure rate.

[0051] Step ②.2: Based on the precoding parameters w obtained in Step ②.1, construct the optimal base station transmit beamformer and fix the receive beamformer. The reflection amplitude is fixed and the projection gradient ascending iterative solution method is used to handle the RIS constant mode constrained CR2 problem.

[0052] Step 2.3: Based on the RIS phase parameters obtained in Step 2.2, the amplitude parameters of RIS are further optimized using the Lagrange multiplier method. The amplification parameter constraint problem in the optimization of the RIS reflection coefficient is handled by using a derivative iterative solution method with a fixed angle.

[0053] Step ②.4: Based on steps ②.1, ②.2, and ②.3, iterate repeatedly to jointly optimize the base station transmit beamformer and RIS parameters; determine whether the result is less than the convergence accuracy threshold or whether the maximum number of iterations has been reached. If so, end the iteration and output the jointly optimized base station transmit beamformer and RIS parameters to maximize the safe rate. Otherwise, continue the iteration.

[0054] ③ For multi-user non-ideal secure communication systems, use iterative optimization algorithms to optimize the precoding parameter w and the RIS phase and amplitude parameters.

[0055] Step 3.1: Optimize the precoding parameters w by fixing the RIS phase parameters and using the Genetic Algorithm (GA) method to solve for the precoding parameters w. In the GA method, each entity is considered a potential solution to the optimization problem. In each iteration, the fitness score of the entity is calculated, and the entities are then sorted. The entity with the highest score is selected as the parent to produce new individuals. The strategy used is either roulette wheel selection or elite selection. A one-point crossover operator is used to exchange value segments between two parent entities in the same generation, thereby producing two new offspring. A bit-flip mutation operator is also used to introduce mutations. The GA algorithm is iterated repeatedly until it reaches convergence. After convergence, the optimal individual within the population is determined through continuous iteration and population evolution.

[0056] Step ③.2: Based on the optimal transmit beamformer obtained in Step ③.1, fix the receive beamformer and use the branch-and-bound method to handle the RIS constant-mode-constrained CR2 problem. By dividing the RIS constant-mode-constrained CR2 problem into smaller subproblems (branches) and solving subproblems that do not meet predetermined criteria (boundaries), the RIS constant-mode-constrained CR2 problem is made non-convex. The branch-and-bound method is applicable to both passive and active RIS scenarios.

[0057] Step ③.3: Based on steps ③.1 and ③.2, iterate repeatedly to jointly optimize the base station transmit beamformer and RIS reflection matrix; determine whether the result is less than the convergence accuracy threshold or whether the maximum number of iterations has been reached. If so, end the iteration and output the jointly optimized base station transmit beamformer and RIS reflection signal matrix, thus obtaining the optimal base station transmit beam and RIS reflection parameters to maximize the safe rate. Otherwise, continue the iteration.

[0058] Beneficial effects:

[0059] 1. This invention discloses a RIS-assisted secure satellite-to-ground communication method with interference, used in a RIS-assisted secure satellite-to-ground communication system. The RIS-assisted secure satellite-to-ground communication system includes a satellite transmitter, a RIS, a UAV (Unmanned Aerial Vehicle), a receiver, and multiple EVEs (External Virtual Machines). The UAV is used to transmit harmful interference signals and construct a secure communication system model. The secure communication system model adds a RIS module to a multi-user covert communication system consisting of a satellite transmitter, multiple receivers (EVEs), and one or more user receivers, which is beneficial for building multiple eavesdropping networks and multi-user collaborative optimization under resource constraints.

[0060] 2. This invention discloses a RIS-assisted secure satellite-to-ground communication method with interference. For RIS-assisted secure communication systems, the method aims to maximize the secure transmission rate. Constraints include satellite transmit power constraint CR1 and RIS constant modulus constraint CR2, constructing an optimization problem for the secure communication system. By using maximizing the secure transmission rate as the optimization objective, it ensures secure communication even for the worst-case receiver in single-user and multi-user communication systems, thereby enabling secure reception for each receiver user while guaranteeing secure communication. The satellite transmit power constraint CR1 ensures effective transmission by the signal transmitter, and the RIS constant modulus constraint CR2 ensures signal reflection. This invention addresses the shortcomings of traditional RIS-based secure satellite-to-ground communication systems, such as low secure transmission rates and poor resource utilization.

[0061] 3. The present invention discloses a RIS-assisted satellite-to-ground secure communication method under interference. Considering active RIS, passive RIS, and non-ideal cases, non-convexization methods are constructed to non-convexize the constant modulus constraint CR2 and the objective function of RIS. The optimization problem of the non-convexized secure communication system is optimized by jointly optimizing the KKT conditions, LogSumExp function, genetic algorithm, Lagrange multipliers, differentiation, branch and bound method, and alternating optimization algorithm to obtain the maximum secure rate of the secure communication system, ensuring that the multi-user secure communication system can still communicate reliably and securely under noise uncertainty. Attached Figure Description

[0062] Figure 1 This is a block diagram of a single-user structure of a RIS-assisted satellite-to-ground secure communication system subject to interference, as described in this invention.

[0063] Figure 2 This is a block diagram of a multi-user structure of a RIS-assisted space-to-ground secure communication system subject to interference, as described in this invention.

[0064] Figure 3 This is a comparison chart of the performance curves of the average secure transmission rate of the method described in this invention under single-user conditions as a function of satellite transmission power and that of traditional methods.

[0065] Figure 4 This is a comparison chart of the performance curves of the average secure transmission rate of the method described in this invention under multi-user conditions as a function of satellite transmission power and that of traditional methods.

[0066] Figure 5 This is a comparison graph of the average secure transmission rate of the method described in this invention under single-user conditions as a function of the number of RIS units, and the performance curve of the traditional method.

[0067] Figure 6 This is a flowchart illustrating the secure communication method described in this invention under different scenarios. Detailed Implementation

[0068] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0069] Example 1

[0070] A three-dimensional coordinate system was established, and the RIS was configured as a uniform rectangular array (URA). The number of RIS reflector units was set to 6, with one user in a single-user scenario and 4 users in a multi-user scenario, along with 4 eavesdroppers (EVEs). The coordinates of the satellite, UAV, and RIS were (0, 200000) meters, (200, 100) meters, and (95, 10) meters, respectively. Furthermore, the user and eavesdroppers were located within a circular area with a radius of 1 meter, with the user centered at (100, 2) and the eavesdroppers centered at (80, 2). The path loss of the signal with distance was set to 20 dB per meter, and the rain attenuation of the satellite was set to 3 dB. The antenna gain of the user was assumed to be 10 dBi.

[0071] For single-user passive RIS secure communication systems, such as Figure 6 As shown in the figure, this embodiment discloses a RIS-assisted satellite-to-ground secure communication method with interference. The specific implementation steps are as follows:

[0072] Step 1: The secure communication system includes a satellite transmitter, a RIS (Radio Recognition System), a UAV (Unmanned Aerial Vehicle), a receiver, and multiple EVEs (External Virtual Machines). The UAV is used to transmit harmful interference signals and construct the secure communication system model. The RIS is used to reflect signals; the user and the EVEs jointly receive signals transmitted by Alice and reflected by the RIS; Willie detects whether Alice is transmitting a useful signal. The secure communication system model includes channel models for the satellite-to-ground communication system, satellite-to-user channel models, satellite-to-EVE channel models, satellite-to-user and EVE channel models, and UAV-to-user channel models.

[0073] Considering rain attenuation and free path loss, the channel model of the satellite-to-ground communication system is expressed as follows:

[0074]

[0075] The satellite-to-user channel model for a RIS-based secure space-to-ground communication system is represented as follows:

[0076]

[0077] The satellite-to-EVE channel model of a RIS-based space-to-ground secure communication system is represented as follows:

[0078]

[0079] In a non-ideal scenario, the channel model for a RIS-based satellite-to-user and EVE communication system is expressed as follows:

[0080]

[0081] The UAV-to-user channel model of a RIS-based space-to-ground secure communication system is represented as follows:

[0082]

[0083] Where: C L λ represents the free space loss. s Let f be the carrier wavelength of the satellite ground channel, f be the overall satellite channel ξ-attenuation, Φ[n] be the phase matrix of RIS, and N be the total number of satellites. R h represents the number of RIS units. SU For direct transmission from satellite users, H SR To access the satellite RIS channel, h RU For direct connection from the user channel, For the i-th EVE channel from the satellite, For the channel from RIS to the i-th EVE, h u For the overall channel from satellite to user, For the ideal channel from satellite to user, Δh u For the channel error from satellite to user, The total channel from the satellite to the i-th EVE, For the ideal channel from the satellite to the i-th EVE, H represents the channel error from the satellite to the i-th EVE. VR For the channel interference from drones to users, h v For the channel between the drone and the RIS.

[0084] Step 2: The satellite transmitter transmits signals via wireless communication, modulating the baseband signal onto the carrier signal; the power of the satellite transmitter satisfies constraint CR1, whereby the total power of the satellite transmitter at the current moment is less than a fixed constraint power.

[0085] The transmitted signal is represented as

[0086] s[n]=w[n](x[n]+n s [n])

[0087] Where: the signal is represented by x, and w is the beamforming data that meets the transmit power constraint requirements.

[0088] Step 3: The user receiver simultaneously receives signals transmitted by the satellite transmitter, interference signals transmitted by the UAV, and signals reflected by the RIS.

[0089] The signal received by the receiver is represented as

[0090] y U [n] = h u s[n]+h ν s in [n]+z l [n]

[0091] in: This is the noise received by the EVE.

[0092] Step 4: The EVE receiver receives signals transmitted by the satellite and signals reflected by the RIS;

[0093] The signal received by the i-th EVE is represented as shown in formula (3);

[0094]

[0095] in: This is the noise received by the user.

[0096] Step 5: For the RIS-assisted secure communication system, with the goal of maximizing the secure rate, and constraints including satellite transmit power constraint CR1 and RIS constant mode constraint CR2, an optimization problem for the secure communication system is constructed. By using the maximization of the secure rate as the optimization objective, secure communication can be achieved even by the worst receiver in both single-user and multi-user communication systems, thereby enabling each receiver user to achieve secure reception while ensuring secure communication. The effective transmission of the signal transmitter is ensured by the satellite transmit power constraint CR1, and the signal reflection is ensured by the RIS constant mode constraint CR2.

[0097] The objective function for the optimization problem of a secure communication system is as follows:

[0098]

[0099]

[0100]

[0101] max R s

[0102] w[n],Φ[n]

[0103] st||w[n]|| 2 ≤P u

[0104]

[0105] Wherein: CR1 is the maximum transmit power constraint, Pu is the maximum transmit power of the transmitter; CR2 is the RIS amplitude constant mode constraint.

[0106] Step Six: According to Jensen's inequality, when considering the constraints, both the RIS constant modulus constraint CR2 and the objective function are non-convex problems that are difficult to solve directly. For single-user passive RIS secure communication systems, single-user active RIS secure communication systems, and multi-user non-ideal secure communication systems, non-convexification methods are constructed to non-convexize the RIS constant modulus constraint CR2 and the objective function, respectively, resulting in the non-convexized secure communication system optimization problem. By jointly optimizing the non-convexized secure communication system optimization problem, the maximum secure rate of the secure communication system is obtained, ensuring that the multi-user secure communication system can still communicate reliably and securely under noise uncertainty.

[0107] ① For a single-user passive RIS secure communication system, an iterative optimization algorithm is used to optimize the precoding parameter w and the RIS phase parameter.

[0108] Step ①.1: Optimize the precoding parameter w by fixing the RIS phase parameters and using the LogSumExp function to transform the objective function of the secure communication system optimization problem into...

[0109]

[0110] The KKT method is used to solve the optimization problem of precoding parameters w, and the optimal solution of precoding parameters w is obtained.

[0111] Step 1.2: Based on step 1.1, obtain the optimal solution of the precoding parameter w, generate the optimal transmit beamformer according to the parameter, fix the receive beamformer, and use the projection gradient ascent method to handle the RIS constant mode constraint CR2 problem.

[0112] Step ①.3: Based on steps ①.1 and ①.2, iterate repeatedly on the secure communication system optimization problem, jointly optimizing the base station transmit beamformer and the RIS reflection matrix; determine whether the result is less than the convergence accuracy threshold, or whether the maximum number of iterations has been reached. If so, end the iteration, output the jointly optimized base station transmit beamformer and RIS reflection signal matrix, thus obtaining the optimal base station transmit beam and RIS reflection parameters, maximizing the secure rate. Otherwise, continue the iteration.

[0113] Example 2

[0114] For single-user active RIS secure communication systems, such as Figure 6 As shown in the figure, this embodiment discloses a RIS-assisted satellite-to-ground secure communication method with interference. The specific implementation steps are as follows:

[0115] Step 1: The secure communication system includes a satellite transmitter, a RIS (Radio Recognition System), a UAV (Unmanned Aerial Vehicle), a receiver, and multiple EVEs (External Virtual Machines). The UAV is used to transmit harmful interference signals and construct the secure communication system model. The RIS is used to reflect signals; the user and the EVEs jointly receive signals transmitted by Alice and reflected by the RIS; Willie detects whether Alice is transmitting a useful signal. The secure communication system model includes channel models for the satellite-to-ground communication system, satellite-to-user channel models, satellite-to-EVE channel models, satellite-to-user and EVE channel models, and UAV-to-user channel models.

[0116] Considering rain attenuation and free path loss, the channel model of the satellite-to-ground communication system is expressed as follows:

[0117]

[0118] The satellite-to-user channel model for a RIS-based secure space-to-ground communication system is represented as follows:

[0119]

[0120] The satellite-to-EVE channel model of a RIS-based space-to-ground secure communication system is represented as follows:

[0121]

[0122] In a non-ideal scenario, the channel model for a RIS-based satellite-to-user and EVE communication system is expressed as follows:

[0123]

[0124] The UAV-to-user channel model of a RIS-based space-to-ground secure communication system is represented as follows:

[0125]

[0126] Where: C L λ represents the free space loss. s Let f be the carrier wavelength of the satellite ground channel, f be the overall satellite channel ξ-attenuation, Φ[n] be the phase matrix of RIS, and N be the total number of satellites. R h represents the number of RIS units. SU For direct transmission from satellite users, H SR To access the satellite RIS channel, h RU For direct connection from the user channel, For the i-th EVE channel from the satellite, For the channel from RIS to the i-th EVE, h u For the overall channel from satellite to user, For the ideal channel from satellite to user, Δh u For the channel error from satellite to user, The total channel from the satellite to the i-th EVE, For the ideal channel from the satellite to the i-th EVE, H represents the channel error from the satellite to the i-th EVE. VR For the channel interference from drones to users, h v For the channel between the drone and the RIS.

[0127] Step 2: The satellite transmitter transmits signals via wireless communication, modulating the baseband signal onto the carrier signal; the power of the satellite transmitter satisfies constraint CR1, whereby the total power of the satellite transmitter at the current moment is less than a fixed constraint power.

[0128] The transmitted signal is represented as

[0129] s[n]=w[n](x[n]+n s [n])

[0130] Where: the signal is represented by x, and w is the beamforming data that meets the transmit power constraint requirements.

[0131] Step 3: The user receiver simultaneously receives signals transmitted by the satellite transmitter, interference signals transmitted by the UAV, and signals reflected by the RIS.

[0132] The signal received by the receiver is represented as

[0133] y U [n] = h u s[n]+h ν s in [n]+z l [n]

[0134] in: This is the noise received by the EVE.

[0135] Step 4: The EVE receiver receives signals transmitted by the satellite and signals reflected by the RIS;

[0136] The signal received by the i-th EVE is represented as shown in formula (3);

[0137]

[0138] in: This is the noise received by the user.

[0139] Step 5: For the RIS-assisted secure communication system, with the goal of maximizing the secure rate, and constraints including satellite transmit power constraint CR1 and RIS constant mode constraint CR2, an optimization problem for the secure communication system is constructed. By using the maximization of the secure rate as the optimization objective, secure communication can be achieved even by the worst receiver in both single-user and multi-user communication systems, thereby enabling each receiver user to achieve secure reception while ensuring secure communication. The effective transmission of the signal transmitter is ensured by the satellite transmit power constraint CR1, and the signal reflection is ensured by the RIS constant mode constraint CR2.

[0140] The objective function for the optimization problem of a secure communication system is as follows:

[0141]

[0142]

[0143]

[0144] max R s

[0145] w[n],Φ[n]

[0146] st||w[n]|| 2 ≤P u

[0147]

[0148] Wherein: CR1 is the maximum transmit power constraint, Pu is the maximum transmit power of the transmitter; CR2 is the RIS amplitude constant mode constraint.

[0149] Step Six: According to Jensen's inequality, when considering the constraints, both the RIS constant modulus constraint CR2 and the objective function are non-convex problems that are difficult to solve directly. For single-user passive RIS secure communication systems, single-user active RIS secure communication systems, and multi-user non-ideal secure communication systems, non-convexification methods are constructed to non-convexize the RIS constant modulus constraint CR2 and the objective function, respectively, resulting in the non-convexized secure communication system optimization problem. By jointly optimizing the non-convexized secure communication system optimization problem, the maximum secure rate of the secure communication system is obtained, ensuring that the multi-user secure communication system can still communicate reliably and securely under noise uncertainty.

[0150] ② For a multi-user active RIS secure communication system, an iterative optimization algorithm is used to optimize the precoding parameter w and the RIS phase and amplitude parameters.

[0151] Step ②.1: Optimize the precoding parameter w by fixing the RIS phase parameters and using the LogSumExp function to define the objective function of the secure communication system optimization problem as follows:

[0152]

[0153] The KKT method is used to solve the optimization problem of precoding parameters w, and the optimal solution of precoding parameters w is obtained.

[0154] Use

[0155] Step ②.2: Based on the optimal solution of the precoding parameter w obtained in Step ②.1, generate the optimal transmit beamformer according to the parameter, fix the receive beamformer, and use the projection gradient ascending iterative solution method to handle the RIS constant mode constrained CR2 problem with the fixed reflection amplitude.

[0156] Step ②.3: Based on the optimal transmit beamformer obtained in Step ②.1, fix the receive beamformer and use a derivative iterative solution method with a fixed angle to handle the amplification parameter constraint problem in the RIS reflection coefficient optimization.

[0157] Step ②.4: Based on steps ②.1, ②.2, and ②.3, iterate repeatedly to jointly optimize the base station transmit beamformer and RIS parameters; determine whether the result is less than the convergence accuracy threshold or whether the maximum number of iterations has been reached. If so, end the iteration and output the jointly optimized base station transmit beamformer and RIS parameters to maximize the safe rate. Otherwise, continue the iteration.

[0158] Example 3

[0159] For multi-user, non-ideal secure communication systems, such as Figure 6 As shown in the figure, this embodiment discloses a RIS-assisted satellite-to-ground secure communication method with interference. The specific implementation steps are as follows:

[0160] Step 1: The secure communication system includes a satellite transmitter, a RIS (Radio Recognition System), a UAV (Unmanned Aerial Vehicle), a receiver, and multiple EVEs (External Virtual Machines). The UAV is used to transmit harmful interference signals and construct the secure communication system model. The RIS is used to reflect signals; the user and the EVEs jointly receive signals transmitted by Alice and reflected by the RIS; Willie detects whether Alice is transmitting a useful signal. The secure communication system model includes channel models for the satellite-to-ground communication system, satellite-to-user channel models, satellite-to-EVE channel models, satellite-to-user and EVE channel models, and UAV-to-user channel models.

[0161] Considering rain attenuation and free path loss, the channel model of the satellite-to-ground communication system is expressed as follows:

[0162]

[0163] The satellite-to-user channel model for a RIS-based secure space-to-ground communication system is represented as follows:

[0164]

[0165] The satellite-to-EVE channel model of a RIS-based space-to-ground secure communication system is represented as follows:

[0166]

[0167] In a non-ideal scenario, the channel model for a RIS-based satellite-to-user and EVE communication system is expressed as follows:

[0168]

[0169] The UAV-to-user channel model of a RIS-based space-to-ground secure communication system is represented as follows:

[0170]

[0171] Where: C L λ represents the free space loss. s Let f be the carrier wavelength of the satellite ground channel, f be the overall satellite channel ξ-attenuation, Φ[n] be the phase matrix of RIS, and N be the total number of satellites. R h represents the number of RIS units. SU For direct transmission from satellite users, H SR To access the satellite RIS channel, h RU For direct connection from the user channel, For the i-th EVE channel from the satellite, For the channel from RIS to the i-th EVE, h u For the overall channel from satellite to user, For the ideal channel from satellite to user, Δh u For the channel error from satellite to user, The total channel from the satellite to the i-th EVE, For the ideal channel from the satellite to the i-th EVE, H represents the channel error from the satellite to the i-th EVE. VR For the channel interference from drones to users, h v For the channel between the drone and the RIS.

[0172] Step 2: The satellite transmitter transmits signals via wireless communication, modulating the baseband signal onto the carrier signal; the power of the satellite transmitter satisfies constraint CR1, whereby the total power of the satellite transmitter at the current moment is less than a fixed constraint power.

[0173] The transmitted signal is represented as

[0174] s[n]=w[n](x[n]+n s [n])

[0175] Where: the signal is represented by x, and w is the beamforming data that meets the transmit power constraint requirements.

[0176] Step 3: The user receiver simultaneously receives signals transmitted by the satellite transmitter, interference signals transmitted by the UAV, and signals reflected by the RIS.

[0177] The signal received by the receiver is represented as

[0178] y U [n] = h u s[n]+h ν s in [n]+z l [n]

[0179] in: This is the noise received by the EVE.

[0180] Step 4: The EVE receiver receives signals transmitted by the satellite and signals reflected by the RIS;

[0181] The signal received by the i-th EVE is represented as shown in formula (3);

[0182]

[0183] in: This is the noise received by the user.

[0184] Step 5: For the RIS-assisted secure communication system, with the goal of maximizing the secure rate, and constraints including satellite transmit power constraint CR1 and RIS constant mode constraint CR2, an optimization problem for the secure communication system is constructed. By using the maximization of the secure rate as the optimization objective, secure communication can be achieved even by the worst receiver in both single-user and multi-user communication systems, thereby enabling each receiver user to achieve secure reception while ensuring secure communication. The effective transmission of the signal transmitter is ensured by the satellite transmit power constraint CR1, and the signal reflection is ensured by the RIS constant mode constraint CR2.

[0185] The objective function for the optimization problem of a secure communication system is as follows:

[0186]

[0187]

[0188]

[0189] max R s

[0190] w[n],Φ[n]

[0191] st||w[n]|| 2 ≤P u

[0192]

[0193] Wherein: CR1 is the maximum transmit power constraint, Pu is the maximum transmit power of the transmitter; CR2 is the RIS amplitude constant mode constraint.

[0194] Step Six: According to Jensen's inequality, when considering the constraints, both the RIS constant modulus constraint CR2 and the objective function are non-convex problems that are difficult to solve directly. For single-user passive RIS secure communication systems, single-user active RIS secure communication systems, and multi-user non-ideal secure communication systems, non-convexification methods are constructed to non-convexize the RIS constant modulus constraint CR2 and the objective function, respectively, resulting in the non-convexized secure communication system optimization problem. By jointly optimizing the non-convexized secure communication system optimization problem, the maximum secure rate of the secure communication system is obtained, ensuring that the multi-user secure communication system can still communicate reliably and securely under noise uncertainty.

[0195] ③ For multi-user non-ideal secure communication systems, use iterative optimization algorithms to optimize the precoding parameter w and the RIS phase and amplitude parameters.

[0196] Step 3.1: Optimize the precoding parameter w by fixing the RIS phase parameters and using the Genetic Algorithm (GA) method to find the optimal solution for the precoding parameter w. In the GA method, each entity is considered a potential solution to the optimization problem. In each iteration, the fitness score of the entity is calculated, and the entities are then sorted. The entity with the highest score is selected as the parent to produce new individuals. The strategy used is either roulette wheel selection or elite selection. A one-point crossover operator is used to exchange value segments between two parent entities in the same generation, thus producing two new offspring. A bit-flip mutation operator is also used to introduce mutations. The GA algorithm is iterated repeatedly until it reaches convergence. After convergence, the optimal individual within the population is determined through continuous iteration and population evolution.

[0197] Step ③.2: Based on the optimal solution of the precoding parameters w obtained in Step ③.1, generate the optimal transmit beamformer according to these parameters, fix the receive beamformer, and use the branch-and-bound method to handle the RIS constant mode constrained CR2 problem. By dividing the RIS constant mode constrained CR2 problem into smaller subproblems (branches) and solving subproblems that do not meet predetermined criteria (boundaries), the RIS constant mode constrained CR2 problem is made non-convex. The branch-and-bound method is applicable to both passive and active RIS scenarios.

[0198] Step ③.3: Based on steps ③.1 and ③.2, iterate repeatedly to jointly optimize the base station transmit beamformer and RIS reflection matrix; determine whether the result is less than the convergence accuracy threshold or whether the maximum number of iterations has been reached. If so, end the iteration and output the jointly optimized base station transmit beamformer and RIS reflection signal matrix, thus obtaining the optimal base station transmit beam and RIS reflection parameters to maximize the safe rate. Otherwise, continue the iteration.

[0199] The above detailed description further illustrates the purpose, technical solution, and beneficial effects of the invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A RIS-assisted satellite-to-ground secure communication method with interference, characterized in that: Includes the following steps, Step 1: The secure communication system includes a satellite transmitter, a Smart Reflector / Smart Metasurface (RIS), a Unmanned Aerial Vehicle (UAV), a receiver, and multiple EVEs (Eavesdroppers). The UAV is used to transmit harmful interference signals and construct the secure communication system model. The RIS is used to reflect signals. Users and EVEs jointly receive signals transmitted by Alice and reflected by the RIS. Willie detects whether Alice is transmitting useful signals. The secure communication system model includes channel models for the satellite-to-ground communication system, satellite-to-user, satellite-to-EVE, satellite-to-user and EVE, and UAV-to-user. Step 2: The satellite transmitter transmits signals via wireless communication, modulating the baseband signal onto the carrier signal; the power of the satellite transmitter satisfies constraint CR1, whereby the total power of the satellite transmitter at the current moment is less than a fixed constraint power; Step 3: The user receiver simultaneously receives the signal transmitted by the satellite transmitter, the interference signal transmitted by the UAV, and the signal reflected by the RIS; Step 4: The EVE receiver receives signals transmitted by the satellite and signals reflected by the RIS; Step 5: For the RIS-assisted secure communication system, with the goal of maximizing the secure rate, and constraints including satellite transmit power constraint CR1 and RIS constant modulus constraint CR2, an optimization problem for the secure communication system is constructed. By using the maximization of the secure rate as the optimization objective, secure communication can be achieved even by the worst receiver in both single-user and multi-user communication systems, thus ensuring secure reception for each receiver user while guaranteeing secure communication. The effective transmission of the signal transmitter is guaranteed by the satellite transmit power constraint CR1, and the signal reflection is guaranteed by the RIS constant modulus constraint CR2. Step Six: For single-user passive RIS secure communication system, single-user active RIS secure communication system, and multi-user non-ideal secure communication system, construct non-convexification methods to process the RIS constant modulus constraint CR2 and objective function respectively, and obtain the non-convex secure communication system optimization problem. Jointly optimize the non-convex secure communication system optimization problem to obtain the maximum secure rate of the secure communication system, ensuring that the multi-user secure communication system can still communicate reliably and securely under the condition of noise uncertainty.

2. The RIS-assisted secure satellite-to-ground communication method with interference as described in claim 1, characterized in that: In step one, Considering rain attenuation and free path loss, the channel model of the satellite-to-ground communication system is expressed as follows: The satellite-to-user channel model for a RIS-based secure space-to-ground communication system is represented as follows: The satellite-to-EVE channel model of a RIS-based space-to-ground secure communication system is represented as follows: In a non-ideal scenario, the channel model for a RIS-based satellite-to-user and EVE communication system is expressed as follows: The UAV-to-user channel model of a RIS-based space-to-ground secure communication system is represented as follows: Where: C L Let f represent the free space loss, ξ represent the overall satellite channel loss, Φ[n] represent the rain attenuation, and h represent the phase matrix of the RIS. SU For direct transmission from satellite users, H SR To access the satellite RIS channel, h RU For direct connection from the user channel, For the i-th EVE channel from the satellite, For the channel from RIS to the i-th EVE, h u For the overall channel from satellite to user, For the ideal channel from satellite to user, Δh u For the channel error from satellite to user, Let i be the total channel from the satellite to the i-th EVE. Let be the channel error from the satellite to the i-th EVE. For the ideal channel from the satellite to the i-th EVE, H VR For the channel interference from drones to users, h v For the channel between the drone and the RIS.

3. The RIS-assisted secure satellite-to-ground communication method as described in claim 2, characterized in that: In step two, the transmitted signal is represented as s[n]=w[n](x[n]+n s [n]) Where: the signal is represented by x, and w is the precoding parameter.

4. The RIS-assisted secure satellite-to-ground communication method as described in claim 3, characterized in that: In step three, the signal received by the receiver is represented as follows: y U [n]=h u s[n]+h ν s in [n]+z l [n] in: This is the noise received by EVE.

5. The RIS-assisted secure space-to-ground communication method as described in claim 4, characterized in that: In step four, the signal received by the i-th EVE is represented as: in: It is the noise received by the user.

6. The RIS-assisted secure satellite-to-ground communication method as described in claim 5, characterized in that: In step five, the objective function of the secure communication system optimization problem is as follows: Where: CR1 is the maximum transmit power constraint, P u CR2 represents the maximum transmit power of the transmitter; CR2 represents the RIS amplitude constant mode constraint.

7. A RIS-assisted secure satellite-to-ground communication method as described in claim 6, characterized in that: In step six, ① For a single-user passive RIS secure communication system, an iterative optimization algorithm is used to optimize the precoding parameter w and the RIS phase parameter; Step ①.1: Optimize the precoding parameter w by fixing the RIS phase parameters and using the LogSumExp function to transform the objective function of the secure communication system optimization problem into... The optimal solution for the precoding parameter w is obtained by using the KKT method, thereby obtaining the maximum secure rate; Step 1.2: Based on the precoding parameters obtained in Step 1.1, construct the optimal base station transmit beamformer and fix the receive beamformer. Use the projection gradient ascent method to handle the RIS constant mode constraint CR2 problem and solve for the optimal RIS phase parameters. Step ①.3: Based on steps ①.1 and ①.2, iterate repeatedly on the optimization problem of the secure communication system, jointly optimizing the base station transmit beamformer and the RIS reflection matrix; determine whether the result is less than the convergence accuracy threshold, or whether the maximum number of iterations has been reached. If so, end the iteration, output the jointly optimized base station transmit beamformer and RIS reflection signal matrix, that is, obtain the optimal base station transmit beam and RIS reflection parameters, and maximize the security rate; otherwise, continue the iteration. ② For a single-user active RIS secure communication system, an iterative optimization algorithm is used to optimize the precoding parameter w and the RIS phase and amplitude parameters; Step ②.1: Optimize the precoding parameter w by fixing the RIS phase parameters and using the LogSumExp function to define the objective function of the secure communication system optimization problem as follows: The optimal solution for the precoding parameters is obtained by using the KKT method, thereby obtaining the maximum secure rate; Step ②.2: Based on the precoding parameters obtained in Step ②.1, construct the optimal base station transmit beamformer and fix the receive beamformer. The reflection amplitude is fixed and the projection gradient ascending iterative solution method is used to handle the RIS constant mode constraint CR2 problem. Step ②.3: Based on the RIS phase parameters obtained in Step ②.2, the amplitude parameters of RIS are further optimized using the Lagrange multiplier method. The amplification parameter constraint problem in the optimization of the RIS reflection coefficient is handled by using the derivative iterative solution method with a fixed angle. Step ②.4: Based on steps ②.1, ②.2, and ②.3, iterate repeatedly to jointly optimize the base station transmit beamformer and RIS parameters; determine whether the result is less than the convergence accuracy threshold or whether the maximum number of iterations has been reached. If so, end the iteration and output the jointly optimized base station transmit beamformer and RIS parameters to maximize the safe rate; otherwise, continue the iteration. ③ For multi-user non-ideal secure communication systems, use iterative optimization algorithms to optimize the precoding parameter w and the RIS phase and amplitude parameters; Step 3.1: Optimize the precoding parameters w by fixing the RIS phase parameters and solve the encoding parameters w using the Genetic Algorithm (GA) method. In the GA method, each entity is considered as a potential solution to the optimization problem. In each iteration, the fitness score of the entity is calculated, and the entities are then sorted. The entity with the highest score is selected as the parent to generate new individuals. The strategy employed is either roulette wheel selection or elite selection; a one-point crossover operator is used to exchange value segments between two parent entities in the same generation, thereby generating two new offspring; a bit-flip mutation operator is also used to introduce mutations; the genetic algorithm GA is iterated repeatedly until the genetic algorithm GA reaches convergence; after convergence, the optimal individual in the population is determined through continuous iteration and population evolution. Step ③.2: Based on the optimal transmit beamformer obtained in Step ③.1, fix the receive beamformer and use the branch and bound method to handle the RIS constant mode constraint CR2 problem; by dividing the RIS constant mode constraint CR2 problem into multiple sub-problems and solving sub-problems that do not meet the predetermined criteria, the RIS constant mode constraint CR2 problem is made non-convex; the branch and bound method is applicable to both passive and active RIS scenarios. Step 3.3: Based on steps 3.1 and 3.2, iterate repeatedly to jointly optimize the base station transmit beamformer and RIS reflection matrix; determine whether the result is less than the convergence accuracy threshold or whether the maximum number of iterations has been reached. If so, end the iteration and output the jointly optimized base station transmit beamformer and RIS reflection signal matrix, thus obtaining the optimal base station transmit beam and RIS reflection parameters to maximize the safe rate; otherwise, continue the iteration.

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