Secret rate optimization method and system for secure wireless communication system based on active intelligent reflecting surface, and storage medium

Abstract

The invention discloses a secure wireless communication system secrecy rate optimization method and system based on an active intelligent reflecting surface, and a storage medium, relates to the field of wireless communication, and aims to solve the problem of lack of the secure wireless communication system secrecy rate optimization method based on the active intelligent reflecting surface in the prior art. Comprising the following steps: step 1, based on optimization of beam forming at a multi-antenna access point and reflected beam forming at an intelligent reflecting surface, constructing a secure wireless communication system secrecy rate optimization model based on the active intelligent reflecting surface; 2, taking the optimization model as a fitness function, initializing a quantum seal group algorithm, obtaining the position of a quantum hunting through a mapping rule, and calculating the fitness; 3, calculating a conversion control coefficient; 4, evaluating the target fitness function, and enabling the quantum civilian group to find a better quantum position; and step 5, repeatedly executing the step 3 to the step 4 until the maximum number of iterations is reached.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technologies, and in particular, to a method, a system, and a storage medium for optimizing the secrecy rate of a secure wireless communication system based on an active intelligent reflecting surface. Background Art

[0002] At present, the physical layer security in wireless communication has been deeply studied. The key feature of an active intelligent reflecting surface is that each reflecting unit is equipped with a power amplifier, so that the phase and amplification factor of a signal can be adjusted simultaneously at the cost of an additional power supply. For the wireless communication scenario based on an active intelligent reflecting surface, "Power allocation for energy efficiency and secrecy of wireless interference networks" published by Sheng, Zhichao, etc. in 《IEEE Transactions on Wireless Communications》(2018, vol.17, no.6, pp.3737 - 3751) proposed a multi - user interference wireless communication system with eavesdroppers, aiming to optimize the worst secrecy throughput in the network link through power allocation, but did not consider the problem of improving the secrecy rate of a wireless communication system based on an intelligent reflecting surface. "Secure wireless communication via intelligent reflecting surface" published by Cui, Miao, etc. in 《IEEE Wireless Communications Letters》(2019, vol.8, no.5, pp.1410 - 1414) proposed a method for improving the secrecy rate of a secure wireless communication system based on an intelligent reflecting surface, but the intelligent reflecting surface model adopted passive reflecting units and did not consider the method for optimizing the secrecy rate of a secure wireless communication system based on an active intelligent reflecting surface.

[0003] Currently, the research on the method for optimizing the secrecy rate of a secure wireless communication system based on an active intelligent reflecting surface is still in its infancy, and the method for optimizing the secrecy rate of a secure wireless communication system based on an active intelligent reflecting surface needs to be further studied. Summary of the Invention

[0004] The technical problem to be solved by the present invention is:

[0005] In the prior art, there is a lack of a method for optimizing the secrecy rate of a secure wireless communication system based on an active intelligent reflecting surface.

[0006] The technical solution adopted by the present invention to solve the above - mentioned technical problem:

[0007] The present invention provides a method for optimizing the secrecy rate of a secure wireless communication system based on an active intelligent reflecting surface, including the following steps:

[0008] Step 1: Based on the optimization of beamforming at the multi-antenna access point and reflection beamforming at the intelligent reflecting surface, construct an optimization model for the secrecy rate of the secure wireless communication system based on the active intelligent reflecting surface;

[0009] Step 2: Use the optimization model for the secrecy rate of the secure wireless communication system based on the active intelligent reflecting surface as the fitness function, initialize the quantum snow leopard swarm algorithm, obtain the position of the quantum cheetah through the mapping rule, and calculate the fitness;

[0010] Step 3: Calculate the conversion control coefficient;

[0011] Step 4: Evaluate the target fitness function to enable the quantum snow leopard swarm to find a better quantum position;

[0012] Step 5: If the number of iterations is less than the preset maximum number of iterations, let t = t + 1, and return to Step 3; otherwise, terminate the iteration, output the global optimal quantum position of the quantum snow leopard swarm, obtain the position according to the mapping rule, return the optimal fitness value, and finally obtain the method for optimizing the secrecy rate of the secure wireless communication system based on the active intelligent reflecting surface.

[0013] Further, Step 1 includes the following process:

[0014] The channel coefficients from the multi-antenna access point to the intelligent reflecting surface, from the multi-antenna access point to the user, from the multi-antenna access point to the eavesdropper, from the intelligent reflecting surface to the user, and from the intelligent reflecting surface to the eavesdropper are respectively expressed as and The beamforming vector is expressed as which satisfies ||ω|| 2 ≤P T , where P T is the maximum transmission power of the multi-antenna access point;

[0015] Model the reflection using intelligent reflecting surface elements, expressed as:

[0016] q = [q1, q2,..., q N

[0017] where ψ n ∈[0, 2π) represents the phase shift coefficient of the nth reflection unit, where n = 1, 2,..., N, and N is the number of intelligent reflecting surfaces of the reflection units;

[0018] The signals received by the user and the eavesdropper are respectively expressed as:

[0019] ​y UA = (h AU + h IU QH AI )ω + h IU Qn I + n U

[0020] y EA = (h AE + h IE QH AI )ω + h IE Qn I + n E

[0021] where Q = diag(q) represents a diagonal matrix, diag(·) represents the diagonal operation, and its diagonal elements are the corresponding elements of the vector q. n U and n E are the Gaussian noises at the user and the eavesdropper respectively, with zero mean and variances of and is the thermal noise generated by the intelligent reflecting surface with variance , where I represents the identity matrix;

[0022] The secrecy rate from the multi-antenna access point to the user is expressed as:

[0023] R sec = [R UA - R EA +

[0024] where [z] + = max(z, 0), which means that if z ≥ 0, the final result takes z; if z < 0, the final result takes 0. The achievable secrecy rates of the legitimate link and the eavesdropping link of the active intelligent reflecting surface-assisted secure wireless communication system are respectively:

[0025]

[0026]

[0027] By jointly optimizing the multi-antenna access point transmission beamforming vector ω and the intelligent reflecting surface reflection beamforming vector Q, a secrecy rate optimization model for the active intelligent reflecting surface-based secure wireless communication system is constructed:

[0028] Taking the secrecy rate optimization problem of the active intelligent reflecting surface-based secure wireless communication system as the objective function:

[0029]

[0030] ​The constraint conditions are as follows:

[0031] ||ω|| 2 ≤P T

[0032]

[0033] |Q[j,j]|≤η j

[0034] where ω is the transmit beamforming vector of the multi-antenna access point, and P I is the maximum amplification power budget of the intelligent reflecting surface, and η j > 1 is the maximum amplification coefficient of the j-th reflecting element.

[0035] Furthermore, Step 2 includes the following process:

[0036] Initialize the population size K of the quantum snow leopard swarm, the search space dimension D of each quantum snow leopard, and the maximum number of iterations;

[0037] Let the quantum position of the i-th quantum snow leopard in the t-th generation be represented as where Obtain the position of the i-th quantum snow leopard according to the mapping rule The specific mapping rule is: where U d and L d represent the upper and lower bounds of the d-th dimension of the search interval of the quantum snow leopard swarm; Calculate the fitness of the position of the i-th quantum snow leopard in the t-th generation through the fitness function of the secure wireless communication system secrecy rate optimization model based on the active intelligent reflecting surface

[0038] Furthermore, Step 3 includes the following steps:

[0039] Calculate the parameter r t as:

[0040]

[0041] where r is the maximum number of iterations and S is the auditory feature factor;

[0042] Calculate the conversion control coefficient χ as:

[0043]

[0044] where is a random number uniformly distributed between 0 and 1.

[0045] Furthermore, Step 4 includes the following process:

[0046] ​The quantum sensitivity range r of each cheetah is:

[0047]

[0048] When |χ| ≤ 1, the quantum snow leopard is guided to attack the prey; otherwise, the task of the quantum snow leopard is to find new possible solutions globally; in the quantum snow leopard population, the best candidate quantum snow leopard is randomly generated, denoted as The best quantum position in the t-th cycle is denoted as

[0049] Calculate as:

[0050]

[0051] The d-dimensional quantum rotation angle of the i-th quantum snow leopard is updated as:

[0052]

[0053] where θ is a randomly selected angle, and ε t represents the weight inertia coefficient, specifically:

[0054]

[0055] where ε max and ε min are the upper and lower limits of ε t respectively;

[0056] Update the quantum position of each quantum snow leopard:

[0057]

[0058] The present invention also provides a secrecy rate optimization system for a secure wireless communication system based on an active intelligent reflecting surface. The system has program modules corresponding to the steps of the method described in any one of the above technical solutions, and when running, executes the steps in the secrecy rate optimization method for the secure wireless communication system based on the active intelligent reflecting surface described above.

[0059] The present invention also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and the computer program is configured to implement the steps in the secrecy rate optimization method for the secure wireless communication system based on the active intelligent reflecting surface described in any one of the above technical solutions when called by a processor.

[0060] Compared with the prior art, the beneficial effects of the present invention are:

[0061] A method for optimizing the secrecy rate of a secure wireless communication system based on an active intelligent reflecting surface. In an intelligent reflecting surface-assisted secure wireless communication system, the secrecy rate of users is improved by jointly optimizing the beamforming at the multi-antenna access point and the reflecting beamforming at the intelligent reflecting surface. The present invention applies the quantum snow leopard swarm algorithm to the problem of optimizing the secrecy rate of a secure wireless communication system based on an active intelligent reflecting surface, significantly improving the search accuracy and search speed.

[0062] The quantum snow leopard swarm algorithm of the present invention is superior to existing swarm intelligence algorithms in terms of convergence speed and convergence accuracy, providing a promising solution for solving optimization problems in engineering practice, having significant advantages in solving complex and high-dimensional optimization problems, and can be widely applied in a wider range of engineering environments. Description of the Drawings

[0063] Figure 1 Schematic diagram of the method for improving the secrecy rate of an active intelligent reflecting surface secure wireless communication system based on the quantum snow leopard swarm algorithm and the snow leopard swarm algorithm in an embodiment of the present invention;

[0064] Figure 2 Curve graph showing the change of the secrecy rate of an active intelligent reflecting surface secure wireless communication system based on the quantum snow leopard swarm algorithm (QSCSO) and the snow leopard swarm algorithm (SCSO) with the number of iterations in an embodiment of the present invention, where M = 4 and N = 64 are set;

[0065] Figure 3 Curve graph showing the change of the secrecy rate of an active intelligent reflecting surface secure wireless communication system based on the quantum snow leopard swarm algorithm and the snow leopard swarm algorithm with the number of iterations in an embodiment of the present invention, where M = 8 and N = 128 are set;

[0066] Figure 4 Curve graph showing the change of the secrecy rate of an active intelligent reflecting surface secure wireless communication system based on the quantum snow leopard swarm algorithm and the snow leopard swarm algorithm with the number of access point antennas in an embodiment of the present invention;

[0067] Figure 5 Curve graph showing the change of the secrecy rate of an active intelligent reflecting surface secure wireless communication system based on the quantum snow leopard swarm algorithm and the snow leopard swarm algorithm with the number of reflecting units of the intelligent reflecting surface in an embodiment of the present invention. Detailed Embodiment

[0068] To enable those skilled in the art to better understand the solution of the present invention, the exemplary embodiments or examples of the present invention will be described below in conjunction with the accompanying drawings. Obviously, the described embodiments or examples are only a part of the embodiments or examples of the present invention, rather than all of them. All other embodiments or examples obtained by those of ordinary skill in the art based on the embodiments or examples in the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0069] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following detailed description of the specific embodiments of the present invention will be given in conjunction with the accompanying drawings.

[0070] Specific Embodiment 1: The present invention provides a method for optimizing the secrecy rate of a secure wireless communication system based on an active intelligent reflecting surface, as Figure 1 shown, including the following steps:

[0071] Step 1: Based on the optimization of beamforming at a multi-antenna access point and reflected beamforming at an intelligent reflecting surface, construct an optimization model for the secrecy rate of a secure wireless communication system based on an active intelligent reflecting surface;

[0072] Step 2: Use the optimization model for the secrecy rate of a secure wireless communication system based on an active intelligent reflecting surface as the fitness function, initialize the quantum snow leopard swarm algorithm, obtain the position of the quantum cheetah through the mapping rule, and calculate the fitness;

[0073] Step 3: Calculate the conversion control coefficient;

[0074] Step 4: Evaluate the target fitness function to enable the quantum snow leopard swarm to find a better quantum position;

[0075] Step 5: If the number of iterations is less than the preset maximum number of iterations, let t = t + 1, and return to Step 3; otherwise, terminate the iteration, output the global optimal quantum position of the quantum snow leopard swarm, obtain the position according to the mapping rule, return the optimal fitness value, and finally obtain the method for optimizing the secrecy rate of a secure wireless communication system based on an active intelligent reflecting surface.

[0076] The present invention considers secure communication from a multi - antenna access point (AP) to a single - antenna user, with a single - antenna eavesdropper. First, the received signal power of the intelligent reflecting surface is increased by adjusting the phase - shift units of the intelligent reflecting surface or by increasing the length of the reflected signal from the intelligent reflecting surface and the non - reflected signal from the user. At the same time, the received signal is eliminated by adding the received signal to the reflected signal from the eavesdropper, both of which can improve the secrecy rate of the user. In addition, the beamforming transmitted by the multi - antenna access point can be designed to achieve a balance between the signal power directed at the intelligent reflecting surface and the signal power directed at the single - antenna user or the single - antenna eavesdropper respectively, so as to enhance or weaken the signal. Therefore, by jointly optimizing the beamforming at the multi - antenna access point and the reflected beamforming at the intelligent reflecting surface, the secrecy rate of the user can be maximized.

[0077] Specific implementation method 2: Step 1 includes the following process:

[0078] Considering the communication between a multi - antenna access point with M antennas and a single - antenna user in the presence of a single - antenna eavesdropper. Deploy an intelligent reflecting surface with N reflecting elements to assist the secure communication between the multi - antenna access point and the user. The intelligent reflecting surface is equipped with a controller for coordinating channel acquisition and data transmission between the multi - antenna access point and the intelligent reflecting surface. The channel coefficients from the multi - antenna access point to the intelligent reflecting surface, from the multi - antenna access point to the user, from the multi - antenna access point to the eavesdropper, from the intelligent reflecting surface to the user, and from the intelligent reflecting surface to the eavesdropper are respectively denoted as and The multi - antenna access point sends a confidential message to the user. The beamforming vector is denoted as which satisfies ||ω|| 2 ≤P T , where P T is the maximum transmit power of the multi - antenna access point. Each unit of the intelligent reflecting surface reflects the received signal from the multi - antenna access point with an adjustable phase shift.

[0079] The reflection of the intelligent reflecting surface unit is modeled as:

[0080] q = [q1, q2,..., q N

[0081] where represents the phase - shift coefficient of the nth reflecting unit, where n = 1, 2,..., N, and N is the number of reflecting units of the intelligent reflecting surface;

[0082] For an active intelligent - reflecting - surface - assisted secure wireless communication system, the signals received by the user and the eavesdropper are respectively expressed as:

[0083] y UA =(h AU ​+h IU QH AI )ω+h IU Qn I +n U

[0084] y EA =(h AE +h IE QH AI )ω+h IE Qn I +n E

[0085] where \(Q = \text{diag}(q)\) represents a diagonal matrix, \(\text{diag}(\cdot)\) represents the diagonal operation, and its diagonal elements are the corresponding elements of the vector \(q\), \(n\) U and \(n\) E are the Gaussian noises at the user and the eavesdropper respectively, with zero mean and variances of and is the thermal noise generated by the intelligent reflecting surface with variance , where \(I\) represents the identity matrix;

[0086] The secrecy rate from the multi - antenna access point to the user is expressed as:

[0087] R sec =[R UA -R EA +

[0088] where \([z]\) + =\(\max(z, 0)\), which means that if \(z\geq0\), the final result takes \(z\); if \(z < 0\), the final result takes \(0\). The achievable secrecy rates of the legitimate link and the eavesdropping link of the active intelligent reflecting surface - assisted secure wireless communication system are respectively:

[0089]

[0090] For the active intelligent reflecting surface - assisted secure wireless communication system, the goal is to maximize the secrecy rate by jointly optimizing the transmit beamforming vector \(\omega\) of the multi - antenna access point and the reflecting beamforming vector \(Q\) of the intelligent reflecting surface. Construct the secrecy rate optimization model of the active intelligent reflecting surface - based secure wireless communication system:

[0091] Take the secrecy rate optimization problem of the active intelligent reflecting surface - based secure wireless communication system as the objective function:

[0092]

[0093] The constraint conditions are:

[0094] ​||ω|| 2 ≤P T

[0095]

[0096] |Q[j,j]| ≤ η j

[0097] where ω is the transmit beamforming vector of the multi - antenna access point, and P I is the maximum amplification power budget of the intelligent reflecting surface, and η j > 1 is the maximum amplification coefficient of the j - th reflecting element.

[0098] Other parts of this implementation scheme are the same as those of the first specific implementation scheme.

[0099] Specific implementation scheme three: Step two includes the following process:

[0100] Initialize the population size K of the quantum snow leopard population, the search space dimension D of each quantum snow leopard (representing the dimension of the problem to be solved), and the maximum number of iterations;

[0101] Let the quantum position of the i - th quantum snow leopard in the t - th generation be represented as where Obtain the position of the i - th quantum snow leopard according to the mapping rule The specific mapping rule is: where U d and L d represent the upper and lower bounds of the d - th dimension of the search interval of the quantum snow leopard population. The quantum position of each quantum snow leopard corresponds to an optimization scheme for the secrecy rate of the secure wireless communication system based on the active intelligent reflecting surface. Calculate the fitness of the position of the i - th quantum snow leopard in the t - th generation through the fitness function of the optimization model of the secrecy rate of the secure wireless communication system based on the active intelligent reflecting surface. After generating the initial quantum snow leopard population position, use the optimization problem of the secrecy rate of the secure wireless communication system based on the active intelligent reflecting surface as the objective function to evaluate it, and calculate the fitness of the position of the i - th quantum snow leopard in the t - th generation through the fitness function Calculate the fitness of the position of the i - th quantum snow leopard in the t - th generation, and at the same time its value also represents the fitness of the corresponding quantum position of the i - th quantum snow leopard in the t - th generation. Other parts of this implementation scheme are the same as those of the second specific implementation scheme.

[0102] Specific implementation scheme four: Step three includes the following steps:

[0103] As the quantum snow leopard population searches for prey, according to the working mechanism of the proposed algorithm, the value of the parameter r t will linearly decrease from 2 to 0 to approach the prey it is seeking without losing or ignoring it.

[0104] Calculate the parameter r t is:

[0105]

[0106] where T is the maximum number of iterations, and S is the auditory feature factor, whose value is determined by the auditory characteristics of the quantum snow leopard;

[0107] Calculate the conversion control coefficient χ as:

[0108]

[0109] where is a random number uniformly distributed between 0 and 1. Other parts of this implementation are the same as those of the third specific implementation.

[0110] Specific implementation five: Step four includes the following process:

[0111] The quantum sensitivity range r of each snow leopard is:

[0112]

[0113] When |χ| ≤ 1, the quantum snow leopard is guided to attack the prey; otherwise, the task of the quantum snow leopard is to find new possible solutions globally; in the quantum snow leopard group, a best candidate quantum snow leopard is randomly generated, denoted as The best quantum position in the t-th cycle is denoted as

[0114] Calculate as:

[0115]

[0116] The d-dimensional quantum rotation angle of the i-th quantum snow leopard is updated as:

[0117]

[0118] where θ is a randomly selected angle, and ε t represents the weight inertia coefficient, specifically:

[0119]

[0120] where ε max and ε min are the upper and lower limits of ε t respectively;

[0121] Update the quantum position of each quantum snow leopard:

[0122]

[0123] Other aspects of this implementation are the same as those of Specific Implementation 4.

[0124] The secrecy rate optimization method (algorithm) of a secure wireless communication system based on an active intelligent reflecting surface proposed by the present invention is the underlying technical core of the present invention. Various products can be derived based on this algorithm.

[0125] Based on the method proposed by the present invention, a secrecy rate optimization system for a secure wireless communication system based on an active intelligent reflecting surface is developed using a programming language. This system has program modules corresponding to the steps of the above technical solution and executes the steps in the above secrecy rate optimization method for a secure wireless communication system based on an active intelligent reflecting surface when running.

[0126] The computer program of the developed system (software) is stored on a computer-readable storage medium. The computer program is configured to implement the steps of the above secrecy rate optimization method for a secure wireless communication system based on an active intelligent reflecting surface when called by a processor. That is, the present invention is materialized on a carrier to become a computer program product.

[0127] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuitry, integrated circuit systems, application specific integrated circuits (ASICs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special or general programmable processor that receives data and instructions from a storage system, at least one input device, and at least one output device, and transmits the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0128] The computing programs (also referred to as programs, software, software applications, or code) in the present invention include machine instructions for a programmable processor and can be implemented using high-level procedural and / or object-oriented programming languages and / or assembly / machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, device, and / or apparatus (e.g., magnetic disks, optical disks, memories, programmable logic devices PLD) for providing machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0129] The beneficial effects of the present invention will be described below in conjunction with specific embodiments.

[0130] Example 1

[0131] For the secure wireless communication system based on the active intelligent reflecting surface, the parameter settings of the method for improving the secrecy rate of the active intelligent reflecting surface secure wireless communication system based on the quantum snow leopard swarm mechanism are as follows: the population size K of the quantum snow leopard swarm is 50, the auditory feature factor S is 2, and the selected random angle θ is between 0 and 360. The initial quantum positions of the quantum snow leopard swarm are randomly generated within the quantum position domain. To facilitate the comparison of the performance of the proposed quantum snow leopard swarm mechanism, the traditional snow leopard swarm algorithm [1] is applied to solve the secrecy rate optimization problem of the active intelligent reflecting surface secure wireless communication system in this embodiment for comparison, and the population sizes of the two are set to the same value, and the maximum number of iterations is 1000 times for both. All results are the means of 100 simulation experiments.

[0132] Through Figure 2 and Figure 3 It can be seen that the secrecy rate of the quantum snow leopard swarm algorithm of the present invention increases with the increase in the number of access point antennas and the number of reflecting elements of the intelligent reflecting surface. In terms of convergence performance, the quantum snow leopard swarm algorithm is significantly superior to the snow leopard swarm algorithm.

[0133] As Figure 4 shown, in the simulation, the number of access point antennas increases from 3 to 10. With the increase in the number of access point antennas, the secrecy rate basically maintains an increasing trend, and the quantum snow leopard swarm algorithm of the present invention always maintains the best performance. When the number of access point antennas is fixed, the secrecy rate can be increased by increasing the number of reflecting units of the intelligent reflecting surface.

[0134] As Figure 5 shown, in the simulation, the number of reflecting units increases from 50 to 140. With the increase in the number of reflecting units of the intelligent reflecting surface, the secrecy rate maintains an increasing trend, and the quantum snow leopard swarm algorithm always performs the best. When the number of reflecting units of the intelligent reflecting surface is fixed, the secrecy rate can be increased by increasing the number of access point antennas.

[0135] Although the present invention is disclosed as above, the protection scope of the present invention is not limited thereto. Those skilled in the art of the present invention can make various changes and modifications without departing from the spirit and scope of the present disclosure, and these changes and modifications will all fall within the protection scope of the present invention.

[0136] The documents cited in the present invention include:

[0137] [1]Seyyedabbasi, Amir, et al. Sand Cat swarm optimization: A nature-inspired algorithm to solve global optimization problems[J]. Engineering with Computers, 2023, pp. 2627-2651.

Claims

1. A method for optimizing the secrecy rate of a secure wireless communication system based on an active intelligent reflecting surface, characterized in that, It includes the following steps: Step 1: Based on the optimization of beamforming at the multi-antenna access point and reflected beamforming at the intelligent reflecting surface, construct a secrecy rate optimization model for the secure wireless communication system based on the active intelligent reflecting surface; Step 2: Use the secrecy rate optimization model of the secure wireless communication system based on the active intelligent reflecting surface as the fitness function, initialize the quantum snow leopard swarm algorithm, obtain the position of the quantum cheetah through the mapping rule, and calculate the fitness; Step 3: Calculate the transformation control coefficient; Step 4: Evaluate the target fitness function to enable the quantum snow leopard swarm to find a better quantum position; Step 5: If the number of iterations is less than the preset maximum number of iterations, let t = t + 1, and return to Step 3; otherwise, the iteration terminates, output the global optimal quantum position of the quantum snow leopard swarm, obtain the position according to the mapping rule, return the optimal fitness value, and finally obtain the secrecy rate optimization method for the secure wireless communication system based on the active intelligent reflecting surface.

2. The method for optimizing the secrecy rate of a secure wireless communication system based on an active intelligent reflecting surface according to claim 1, wherein Step 1 includes the following process: The channel coefficients from the multi-antenna access point to the intelligent reflecting surface, from the multi-antenna access point to the user, from the multi-antenna access point to the eavesdropper, from the intelligent reflecting surface to the user, and from the intelligent reflecting surface to the eavesdropper are respectively denoted as and The beamforming vector is denoted as which satisfies ||ω|| 2 ≤ P T where P T is the maximum transmit power of the multi-antenna access point; Model the reflection using intelligent reflecting surface elements, expressed as: Ding = [q1, q2,..., q N ​ where ψ n ∈ [0, 2π) represents the phase shift coefficient of the nth reflection unit, where n = 1, 2, …, N, and N is the number of reflection units of the intelligent reflecting surface; The signals received by the user and the eavesdropper are respectively expressed as: y UA =(h AU +h IU QH AI )ω + h IU Qn I +n U y EA = (h AE + h IE QH AI )ω + h IE Qn I + n E where \(Q = \text{diag}(q)\) represents a diagonal matrix, \(\text{diag}(\cdot)\) represents the diagonal extraction operation, and its diagonal elements are the corresponding elements of the vector \(q\), \(n\) U and \(n\) E are the Gaussian noises at the user and the eavesdropper respectively, with zero mean and variances of and is the thermal noise generated by the intelligent reflecting surface with a variance of , where \(I\) represents the identity matrix; The secrecy rate from the multi-antenna access point to the user is expressed as: R sec = [R UA - R EA + ​ where [z] + = max(z, 0), which means that if z ≥ 0, the final result is z; If z < 0, the final result takes 0; the achievable secrecy rates of the legitimate link and the eavesdropping link of the secure wireless communication system assisted by the active intelligent reflecting surface are respectively: By jointly optimizing the multi-antenna access point transmit beamforming vector ω and the intelligent reflecting surface reflected beamforming vector Q, construct a secrecy rate optimization model for the secure wireless communication system based on the active intelligent reflecting surface: Take the secrecy rate optimization problem of the secure wireless communication system based on the active intelligent reflecting surface as the objective function: The constraint conditions are: ||ω|| 2 ≤P T |Q[j, j]| ≤ η j where ω is the transmit beamforming vector of the multi-antenna access point, P I is the maximum amplification power budget of the intelligent reflecting surface, and η j > 1 is the maximum amplification coefficient of the i-th reflecting element.

3. The method for optimizing the secrecy rate of the secure wireless communication system based on the active intelligent reflecting surface according to claim 2, wherein Step 2 includes the following process: Initialize the population size K of the quantum snow leopard swarm, the search space dimension D of each quantum snow leopard, and the maximum number of iterations; Let the quantum position representation of the \(i\)-th quantum snow leopard group be \(t\). Where The position of the \(i\)-th quantum snow leopard group is obtained according to the mapping rule The specific mapping rule is as follows: Where \(U\) d and \(L\) d represent the upper and lower bounds of the \(d\)-th dimension of the search interval of the quantum snow leopard group; the fitness of the position of the \(i\)-th quantum snow leopard group in the \(t\)-th generation is calculated through the fitness function of the secrecy rate optimization model of the secure wireless communication system based on the active intelligent reflecting surface Calculate the fitness of the position of the \(i\)-th quantum snow leopard group in the \(t\)-th generation.

4. The method for optimizing the secrecy rate of a secure wireless communication system based on an active intelligent reflecting surface according to claim 3, wherein Step 3 includes the following steps: Calculation parameter r t is as follows: Where T is the maximum number of iterations and S is the auditory feature factor; Calculate the transformation control coefficient χ as: wherein is a random number uniformly distributed between 0 and 1.

5. The method for optimizing the secrecy rate of the secure wireless communication system based on the active intelligent reflecting surface according to claim 4, wherein Step 4 includes the following process: The quantum sensitivity range r of each cheetah is: When |χ| ≤ 1, the quantum snow leopard is guided to attack the prey; otherwise, the task of the quantum snow leopard is to find new possible solutions globally. Among the quantum snow leopard population, the best candidate quantum snow leopard is randomly generated, denoted as The best quantum position in the t-th cycle is denoted as Calculation is as follows: The d-dimensional quantum rotation angle of the i-th quantum snow leopard is updated as: where θ is a randomly selected angle, and ε t represents the weight inertia coefficient, specifically: where ε max and ε min are the upper limit and the lower limit of ε t respectively; Update the quantum position of each quantum snow leopard:

6. A secrecy rate optimization system for a secure wireless communication system based on an active intelligent reflecting surface, characterized in that, The system has program modules corresponding to the steps of the method described in any one of claims 1 to 5 above, and when running, executes the steps in the secrecy rate optimization method for the secure wireless communication system based on the active intelligent reflecting surface described above.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and the computer program is configured to implement the steps in the secrecy rate optimization method for the secure wireless communication system based on the active intelligent reflecting surface described in any one of claims 1 to 5 when called by a processor.

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