A Secure Transmission Method for Wireless Interference Networks Based on Interference Alignment and Artificial Noise

Abstract

The present invention belongs to the field of wireless communication, and particularly relates to a secure transmission method for a wireless interference network based on interference alignment and artificial noise. An interference alignment system including K pairs of legitimate transceivers and T single-antenna eavesdropping nodes is constructed. The transmitting end r transmits useful signals and artificial noise signals, and the remaining transmitting ends only transmit useful signals. The alternating minimization interference alignment algorithm is used to align the interference signals and artificial noise signals to the interference subspace. After interference alignment, the signal-to-noise ratios of the receiving end r and the T eavesdropping nodes are calculated, and an objective function for optimizing the power allocation coefficient and the security outage probability of the transmitting end r is constructed. The optimal power allocation coefficient is obtained by numerically analyzing the objective function, realizing the secure transmission of the wireless interference network under the optimal security outage probability. The alternating minimization interference alignment algorithm of the present invention can be applied to both TDD and FDD systems simultaneously, has a wider applicability, and realizes the flexible allocation of the powers of the useful signals and the AN signals.

Description

Technical Field

[0001] The present invention belongs to the field of wireless communication, and particularly relates to a secure transmission method for a wireless interference network based on interference alignment and artificial noise. Background Art

[0002] Important indicators for measuring the performance of a wireless communication system include reliability, efficiency, security, etc. Interference is a key factor affecting these important indicators. On the one hand, interference will affect the reception quality of the legitimate receiver, thereby reducing the efficiency and reliability of the system; but on the other hand, interference can, to a certain extent, affect potential eavesdropping nodes in the wireless communication network, thereby indirectly improving the reliability of the system and enhancing the secure transmission of the system. Therefore, how to utilize the interference in the wireless communication network to improve the performance of the communication network has become a hot topic in the field of wireless communication research in recent years. With the in-depth research, the academic community has discovered an effective method of using interference, namely interference alignment (IA). For a multiple-input and multiple-output interference broadcast channel (MIMO-IFBC), the interference alignment technology refers to jointly optimizing the precoding matrices at both the transmitter and receiver ends, so as to map the interference overlap in the wireless communication network into a lower subspace, and the remaining interference-free signal space is used to transmit useful information. This not only eliminates the impact of interference on useful information and improves the transmission performance, but also when the number of users is large, interference alignment can greatly improve the degrees of freedom (DoF) of the system.

[0003] Due to the broadcast and superposition characteristics of wireless broadcast channels, many studies also consider using interference alignment to improve physical layer security. "Generalized Interference Alignment" proposed a method for secure communication by using a jammer to assist in transmitting artificial noise (AN) signals in an IA network. Among them, the AN technology reduces the quality of the eavesdropping channel without affecting the quality of the legitimate channel by injecting appropriate noise into the null space of the legitimate channel during the transmission of useful information. "Physical Layer Security Issues in Interference-Alignment-Based Wireless Networks" proposed a solution to combat strong interference using interference alignment and, on this basis, proposed an AN scheme based on the IA network to interfere with external eavesdropping without bringing additional interference to the legitimate network. Due to the need for the transmission system to generate artificial noise additionally, this will increase new constraints on the interference alignment network, thus changing the interference alignment conditions. "Anti-Eavesdropping Schemes for Interference Alignment(IA)-Based Wireless Networks" analyzed the feasibility conditions after adding artificial noise to the interference alignment network and improved it based on the Leakage Minimization (LM) algorithm. However, this article did not make flexible adjustments to the power allocation between the useful signal and AN. "Joint Secure Transceiver Design and Power Allocation for AN-assisted MIMO Networks" proposed to jointly optimize the transceiver precoding matrices of interference and artificial noise in the interference alignment network, solving the power allocation problem between the useful information and artificial noise. However, the optimization problem in this article did not consider the impact of the unknown channel state information (CSI) of the eavesdropping node. Summary of the Invention

[0004] To solve the above problems, the present invention proposes a secure transmission method for a wireless interference network based on interference alignment and artificial noise, and constructs an interference alignment system. The system includes K pairs of legitimate transceivers, each pair of legitimate transceivers has a transmitter and a receiver, and T single-antenna eavesdropping nodes. The single-antenna eavesdropping nodes only eavesdrop on the information of the receiver r. The secure transmission method for the wireless interference network based on interference alignment and artificial noise includes the following steps:

[0005] S1. Initialize the interference alignment system. The transmitting end \(r\) simultaneously sends the useful signal and the artificial noise signal, where \(r\in\{1,2,\cdots,K\}\), and the remaining transmitting ends only send the useful signal;

[0006] S2. Adopt the alternating minimization interference alignment algorithm to align the interference signals and artificial noise signals among all legitimate transceivers in the interference alignment system to the interference subspace;

[0007] S3. After interference alignment, calculate the signal-to-noise ratio of the receiving end \(r\) and the signal-to-noise ratio of \(T\) eavesdropping nodes, and construct an objective function to optimize the power allocation coefficient and the security outage probability of the transmitting end \(r\);

[0008] S4. Analyze the objective function by numerical method to obtain the optimal power allocation coefficient, and achieve secure transmission of the wireless interference network under the optimal security outage probability.

[0009] Furthermore, the process of interference alignment using the alternating minimization interference alignment algorithm is as follows:

[0010] S11. Set the maximum number of iterations and let the number of iterations be equal to 1;

[0011] S12. Calculate the interference matrix among all legitimate transceivers in the interference alignment system, and calculate a set of orthonormal bases of the corresponding receiving end in the interference subspace through the interference matrix;

[0012] S13. Obtain the receiving beamforming vector of the corresponding receiving end and the projection matrix in the interference subspace according to the orthonormal bases;

[0013] S14. Set the interference leakage threshold, calculate the total interference leakage of the interference alignment system according to the orthonormal bases, and judge whether it is greater than the interference leakage threshold. If so, execute step S15; otherwise, output the transmit beamforming vectors, receive beamforming vectors, and artificial noise unit precoding matrices among all legitimate transceivers;

[0014] S15. Calculate the transmit beamforming vector of the corresponding transmitting end through the projection matrix, and obtain the artificial noise unit precoding matrix;

[0015] S16. After the calculation, judge whether the maximum number of iterations is reached. If so, output the transmit beamforming vectors, receive beamforming vectors, and artificial noise unit precoding matrices among all legitimate transceivers; otherwise, increment the number of iterations by 1 and return to step S12.

[0016] Furthermore, the calculation formulas for the interference matrix carried by the transmitting end \(k\), where \(k\in\{1,2,\cdots,K\}\), the orthonormal bases of the receiving end \(k\) in the interference subspace, and the projection matrix are respectively expressed as:

[0017]

[0018] C k = b max [J k ;

[0019]

[0020] Among them, J k represents the interference matrix carried by the transmitting end k, H ki represents the channel matrix from the transmitting end i to the receiving end k, v i represents the transmit beamforming vector of the transmitting end i, H kr represents the channel matrix from the transmitting end r to the receiving end k, V [an]r represents the artificial noise unit precoding matrix transmitted by the transmitting end r, C k represents a set of orthonormal bases of the receiving end k, b max [J k represents the eigenvector corresponding to the largest eigenvalue of the interference matrix J k P k represents the projection matrix of the receiving end k, represents the identity matrix of size N k .

[0021] Furthermore, the calculation formula for the total interference leakage of the interference alignment system is:

[0022]

[0023] Among them, H ki represents the channel matrix from the transmitting end i to the receiving end k, v i represents the transmit beamforming vector of the transmitting end i, C k represents a set of orthonormal bases of the receiving end k, L k represents the interference leakage of the receiving end k.

[0024] Furthermore, the calculation process of step S15 is:

[0025] S21. Update the interference matrix of its corresponding transmitting end through the projection matrix of the receiving end;

[0026] S22. Update the transmit beamforming vector of the corresponding transmitting end according to the updated interference matrix;

[0027] S23. After the update is completed, the receiving end r calculates the artificial noise interference matrix through its updated receive beamforming vector;

[0028] S24. Calculate a new artificial noise unit precoding matrix according to the artificial noise interference matrix.

[0029] Furthermore, the objective function is expressed as:

[0030]

[0031] Among them, the constraint conditions of the objective function are R th represents the minimum security rate of the receiving end r, represents the power coefficient of the useful signal allocated by the transmitting end r, ε represents the security outage probability, and R s is the security rate of the receiving end r, represents the capacity of the main channel at the receiving end r, represents the signal-to-noise ratio at the t-th single-antenna eavesdropping node.

[0032] Furthermore, the signal-to-noise ratio at the t-th single-antenna eavesdropping node is expressed as:

[0033]

[0034] Among them, M r represents the number of antennas of the transmitting end r, h t,r represents the channel vector from the transmitting end r to the single-antenna eavesdropping node t, v r represents the transmit beamforming vector of the transmitting end r, V [an]r represents the artificial noise unit precoding matrix transmitted by the transmitting end r, P represents the transmit power of the other transmitting ends, and P r represents the transmit power of the transmitting end r.

[0035] Advantages of the present invention:

[0036] The present invention proposes a secure transmission method for a wireless interference network based on interference alignment and artificial noise. In this method, an alternating minimization interference alignment algorithm with artificial noise signals is designed. This algorithm does not need to consider the reciprocity of the channel and the distribution of antennas or data streams, and can work in both TDD and FDD systems, with a wider applicability. At the same time, the alternating minimization interference alignment algorithm eliminates the influence of interference on the legitimate receiving end in the system, while severely weakening the quality of the eavesdropping channel and improving the security performance of the system. On this basis, assuming that the transmitting end only knows the channel state information statistically of the eavesdropping nodes, the artificial noise signal is used to reduce the quality of the eavesdropping channel, further improving the secure transmission performance.

[0037] The present invention also considers optimizing the power allocation between the useful signal and the artificial noise signal. Compared with fixing the power ratio of the useful signal and the artificial noise signal, the present invention can flexibly allocate power. Under the constraint conditions of meeting the security rate, the minimization of the security outage probability is achieved. Description of the Drawings

[0038] Figure 1 Flow chart of the secure transmission method for a wireless interference network based on interference alignment and artificial noise according to the present invention;

[0039] Figure 2 Flow chart of the alternating minimization interference alignment algorithm according to the present invention;

[0040] Figure 3 Process diagram for solving the objective function according to the present invention. Detailed implementation manners

[0041] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0042] The present invention proposes a secure transmission method for a wireless interference network based on interference alignment and artificial noise. First, an interference alignment system is constructed. The system includes K pairs of legitimate transceivers. Each pair of legitimate transceivers has a transmitter and a receiver. The transmitter k and the receiver k of the k-th, k ∈ {1, 2,..., K} pair of legitimate transceivers are respectively equipped with M k and N k antennas. There are T single-antenna eavesdropping nodes. All single-antenna eavesdropping nodes are non-collusive eavesdropping, and the eavesdropping channels are independent of each other. The single-antenna eavesdropping nodes only eavesdrop on the information of the receiver r. It is considered that the transmitter can only obtain the channel state information of the eavesdropping nodes.

[0043] The secure transmission method for a wireless interference network based on interference alignment and artificial noise, as Figure 1 shown, includes:

[0044] S1. Initialize the interference alignment system. The transmitter r sends 1 independent data stream, that is, the useful signal, and at the same time uses the remaining M r -1 antennas to send artificial noise signals, r ∈ {1, 2,..., K}. The remaining transmitters only send 1 independent data stream, that is, the useful signal; among them, all transmitters share the same spectrum resource;

[0045] S2. Use the alternating minimization interference alignment algorithm to align the interference signals and artificial noise signals between all legitimate transceivers in the interference alignment system to the interference subspace, so that the receiver only receives the desired useful information;

[0046] Specifically, the interference signal refers to the interference between legitimate transceivers in the interference alignment system. For legitimate transceiver 1 and legitimate transceiver 2 in the interference alignment system, when the transmitting end 1 of legitimate transceiver 1 sends the useful signal corresponding to receiving end 1, this useful signal is an interference signal for receiving end 2. Similarly, the useful signal sent by transmitting end 2 is an interference signal for receiving end 1.

[0047] S3. After interference alignment, calculate the signal-to-noise ratio of receiving end r and the signal-to-noise ratios of T eavesdropping nodes, construct the power allocation coefficient for the useful signal allocated by the optimized transmitting end r, and minimize the objective function of the secure outage probability;

[0048] S4. Analyze the objective function by numerical method to obtain the optimal power allocation coefficient and achieve secure transmission of the wireless interference network under the optimal secure outage probability.

[0049] Specifically, in the interference alignment system, only the transmitting ends of the pair of legitimate transceivers being eavesdropped send useful signals and artificial noise signals simultaneously. In this embodiment, it is assumed that the r-th, r ∈ {1, 2,..., K} pair of legitimate receivers is being eavesdropped. Except for the legitimate transceivers being eavesdropped, the transmitting ends of the remaining legitimate transceivers only send their respective useful signals, and the transmission powers are the same. The antenna configurations of all transmitting ends and receiving ends are the same. At this time, the received signal y of receiving end k, k ∈ {1, 2,..., K} and k ≠ r k is expressed as:

[0050]

[0051] where s k is the data symbol sent by transmitting end k, and s k ~CN(0, 1), and CN(0, 1) represents a complex Gaussian distribution with a mean of 0 and a variance of 1; s l Similarly, represents the receive beamforming vector of receiving end k, and satisfies represents the transmit beamforming vector of transmitting end k, and satisfies v l Similarly, represents the artificial noise unit precoding matrix sent by transmitting end r, and satisfies represents the identity matrix of size M r -1; n k is the additive white Gaussian noise (AWGN) vector of receiving end k, and satisfies represents the identity matrix of size N kThe identity matrix; z r denotes the AWGN artificial noise vector and satisfies Specifically,[[]] denotes the channel matrix from transmitter l to receiver k, which is independent under quasi-static flat fading and whose elements follow a circularly symmetric complex Gaussian distribution (CSCG) with a mean of 0 and a variance of 1, H kk and H [an [[]] kr Similarly.[[]] denotes a complex matrix with N k rows and M l columns,[[]] Similarly.[[]]

[0052] Since the transmitter r needs to transmit the useful signal and the artificial noise signal simultaneously, the transmitted signal s of the transmitter r r is expressed as:[[]]

[0053]

[0054] The received signal corresponding to the receiver r is expressed as:[[]]

[0055]

[0056] where P r denotes the transmit power of the transmitter r, and it is assumed that the transmit powers of the other transmitters are all P,[[]] denotes the power coefficient allocated by the transmitter r to the useful signal, and

[0057] The received signal of the single-antenna eavesdropping node is expressed as:[[]]

[0058]

[0059] where y e,t denotes the received signal of the t-th single-antenna eavesdropping node, h t,k denotes the channel vector from the transmitter k to the single-antenna eavesdropping node t, which follows a CSCG with a mean of 0 and a variance of 1, and n e,t is the AWGN at the single-antenna eavesdropping node t and satisfies n e,t ~CN(0,1).[[]]

[0060] In one embodiment, in order to eliminate the influence of the interference signals and artificial noise signals inherent in the interference alignment system on the legitimate receiver, according to the above-mentioned expression forms of the received signals at the legitimate receiver and the received signals at the single-antenna eavesdropping node, an alternating minimization interference alignment algorithm is designed to align the interference signals and artificial noise signals in the system to the interference subspace, thereby achieving interference alignment. Specifically, as Figure 2 shown, it includes:

[0061] S11. Set the maximum number of iterations, and let the number of iterations be equal to 1;

[0062] S12. Calculate the interference matrices between K pairs of all legitimate transceivers in the interference alignment system, and calculate a set of orthonormal bases of the receiver k, k ∈ {1, 2,..., K} in the interference subspace through the interference matrices;

[0063] Specifically, calculate the interference matrix J k and the orthonormal basis C k The formulas are respectively:

[0064]

[0065] C k = b max [J k ;

[0066] Among them, b max [J k represents the eigenvector corresponding to the largest eigenvalue of the matrix J k .

[0067] S13. Obtain the receive beamforming vector of the receiver k and the projection matrix in the interference subspace according to this set of orthonormal bases;

[0068] Specifically, the receive beamforming vector of the receiver k and the projection matrix P k in the interference subspace are respectively expressed as:

[0069]

[0070] Among them, represents the null space of the matrix .

[0071] S14. Set the interference leakage threshold, calculate the total interference leakage of the interference alignment system according to the orthonormal bases, and judge whether it is greater than the interference leakage threshold. If so, execute step S15; otherwise, output the transmit beamforming vectors v k between all legitimate transceivers, the receive beamforming vectors u k , and the artificial noise unit precoding matrix V [an]r ;

[0072] Specifically, first calculate the interference leakage of each receiver, which is expressed as:

[0073]

[0074] Sum up the interference leakage of all receivers to obtain the total interference leakage of the interference alignment system, which is expressed as:

[0075]

[0076] S15. Calculate the transmit beamforming vector of transmitter k and the artificial noise unit precoding matrix of transmitter r through the projection matrix;

[0077] Specifically, the calculation process includes:

[0078] S21. Update the interference matrix of its corresponding transmitter through the projection matrix of the receiver, which is expressed as:

[0079]

[0080] S22. Update the transmit beamforming vector of the corresponding transmitter according to the updated interference matrix, which is expressed as:

[0081] v k ′ = w min [J k ;

[0082] S23. After the update is completed, receiver r calculates the artificial noise interference matrix through its updated receive beamforming vector, which is expressed as:

[0083]

[0084] S24. Calculate the new artificial noise unit precoding matrix according to the artificial noise interference matrix, which is expressed as:

[0085]

[0086] where, J k ′ represents the updated interference matrix of transmitter k, v k ′ represents the updated transmit beamforming vector of transmitter k, w min [J k ′] represents the eigenvector corresponding to the minimum eigenvalue of the interference matrix J k ′, V [an]r ′ represents the new artificial noise unit precoding matrix, represents taking the eigenvector corresponding to the d-th minimum eigenvalue in the artificial noise interference matrix ;

[0087] After the calculation is completed, it is determined whether the maximum number of iterations is reached. If so, the transmit beamforming vectors v between all legitimate transceivers are output. k , the receive beamforming vectors u k , and the artificial noise unit precoding matrix V [an]r . Otherwise, the number of iterations is incremented by 1 and the process returns to step S12.

[0088] After the above operations, the interference alignment system can ensure that all interference signals and artificial noise signals of the interference alignment system are aligned to the same interference subspace, so that they cannot have an adverse impact on the legitimate receiver.

[0089] In one embodiment, after achieving interference alignment, the received signal at the receiver is simplified, and the signal-to-noise ratio (SNR) at the receiver and the SNR of the single-antenna eavesdropping node are obtained. Then, an optimization problem is established based on the obtained SNR.

[0090] After interference alignment, the interference between legitimate transceivers and the impact of the artificial noise from the transmitter r on the legitimate receiver are eliminated. Therefore, the received signal at the receiver r can be expressed as:

[0091]

[0092] The SNR at the receiver r is expressed as:

[0093]

[0094] The SNR at the t-th single-antenna eavesdropping node is expressed as:

[0095]

[0096] Therefore, the capacity of the main channel at the receiver r can be expressed as:

[0097]

[0098] The channel capacity at the t-th eavesdropping node can be expressed as:

[0099]

[0100] Define the variable R b as the total rate at the receiver r, R s as the secure rate of the receiver r, R e as the rate of redundant information at the receiver r. The secrecy outage probability (SOP) is used as the quality of service criterion at the receiver r, expressed as:

[0101]

[0102] The object of the present invention is to minimize the secrecy outage probability ε by optimizing the power coefficient r allocated to the useful signal under the constraint of a given secrecy terminal rate. Therefore, the optimization problem can be described as:

[0103]

[0104] where R th is the given minimum secrecy rate. Solving the above optimization problem, as Figure 3 shown, includes:

[0105] S101. Analyze the objective function in the optimization problem, transform the probability problem of the objective function into a deterministic problem, and reshape the objective function;

[0106] Specifically, analyze the power allocation coefficient When is fixed, the secrecy outage probability ε will increase with the increase of R s . When ε takes the minimum value, then R s = R th . Therefore, the constraint condition can be transformed into The optimization problem is transformed into:

[0107]

[0108] Using numerical analysis for R th When , a unique feasible solution is obtained, that is, all the power is used to send useful information without generating artificial noise. However, this will lead to a very high secrecy outage. When R th > C b (1), the specified secrecy rate cannot be achieved, so the problem has no solution. Since According to we get The lower bound of Then there is When there is That is, ε = 1, which leads to an inevitable secrecy outage. Therefore, the optimization problem needs to be rewritten as:

[0109]

[0110] Since the T single-antenna eavesdropping nodes are non-colluding eavesdroppers, the SOP can be expressed as:

[0111]

[0112] Among them, the reason from the first equation to the second equation is that the single-antenna eavesdropping node is a non-colluding eavesdropper with independent probabilities; the reason from the second equation to the third equation is to use the complementary cumulative distribution function to transform the probability constraint into a deterministic constraint. is the complementary cumulative distribution function of γ e,t It can be found that minimizing ε is equal to minimizing That is, maximizing Finally, define So the optimization problem can finally be written as:

[0113]

[0114] S102. Transform the reshaped objective function into an implicit function with respect to the power allocation coefficient;

[0115] Specifically, by defining The optimization problem is equivalent to:

[0116]

[0117] Among them, α 1 = M r - 1, α 2 = K - 1.

[0118] S103. Calculate the derivative of the implicit function, and judge whether the function value when the derivative of the implicit function is 1 is less than 0 according to the numerical method. If so, solve the system of equations to output the result. If not, substitute it into the explicit expression of the secrecy outage probability to output the result;

[0119] Specifically, take the derivative of the above optimization problem f to get:

[0120]

[0121] When f'(1) ≥ 0, in order for the transmitter r to meet the transmission requirement of the minimum secrecy rate R th all the power needs to be used to transmit useful information, that is, the transmitter r does not generate artificial noise. Therefore, the optimal solution The corresponding secrecy outage probability is ε = 1 - (1 - e -f(1) ) T ; when f'(1) < 0, the transmitter r can always meet the transmission requirement of the minimum secrecy rate R th At this time, it is necessary to consider reducing the secrecy outage probability. So the transmitter r not only needs to transmit useful information, but also needs to generate artificial noise signals to interfere with the eavesdropping node. Therefore, solve the system of equations:

[0122]

[0123] Get the optimal power allocation coefficient and the corresponding security outage probability ε.

[0124] Regarding the secure transmission problem of MIMO-IFBC, the present invention uses the interference alignment technology to solve the adverse effect of interference on the legitimate receiver in the transmission system. At the same time, considering the actual wireless transmission conditions, since eavesdropping nodes are usually hidden and the transmitter does not know the channel state information of the eavesdropping channel, the artificial noise technology is used to reduce the received signal quality of the eavesdropping node, effectively improving the security of MIMO-IFBC.

[0125] Traditional interference alignment technology based on minimizing interference leakage needs to assume channel reciprocity and is only applicable to time-division duplex (TDD) systems. The alternating minimization (AM) interference alignment algorithm designed in the present invention does not need to assume channel reciprocity, the distribution of antennas or data streams, and can be applied to both TDD and frequency-division duplex (FDD) systems, with a wider range of applicability.

[0126] Finally, compared with fixing the power ratio of the useful signal and the AN signal, the present invention realizes flexible power allocation by optimizing the power allocation between the useful signal and the AN signal assigned by the transmitter.

[0127] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principle and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A secure transmission method for wireless interference networks based on interference alignment and artificial noise, characterized in that, an interference alignment system is constructed, which includes K pairs of legitimate transceivers. Each pair of legitimate transceivers has a transmitter and a receiver, and T single-antenna eavesdropping nodes. The single-antenna eavesdropping nodes only eavesdrop on the information of the receiver r; The secure transmission method for wireless interference networks based on interference alignment and artificial noise includes the following steps: S1. Initialize the interference alignment system. The transmitter r simultaneously sends a useful signal and an artificial noise signal, r ∈ {1, 2,..., K}, and the remaining transmitters only send useful signals; S2. Adopt the alternating minimization interference alignment algorithm to align the interference signals and artificial noise signals between all legitimate transceivers in the interference alignment system to the interference subspace; The process of performing interference alignment using the alternating minimization interference alignment algorithm is as follows: S11. Set the maximum number of iterations and let the number of iterations be equal to 1; S12. Calculate the interference matrix between all legitimate transceivers in the interference alignment system, and calculate a set of orthonormal bases of the corresponding receiver in the interference subspace through the interference matrix; S13. Obtain the receive beamforming vector of the corresponding receiver and the projection matrix in the interference subspace according to the orthonormal basis; The calculation formulas for the interference matrix carried by the transmitter k, k ∈ {1, 2,..., K}, the orthonormal basis of the receiver k in the interference subspace, and the projection matrix are respectively expressed as: C k = b max [J k ; Among them, J k represents the interference matrix carried by the transmitting end k, H ki represents the channel matrix from the transmitting end i to the receiving end k, v i represents the transmit beamforming vector of the transmitting end i, H kr represents the channel matrix from the transmitting end r to the receiving end k, V [an]r represents the artificial noise unit precoding matrix transmitted by the transmitting end r, C k represents a set of orthonormal bases of the receiving end k, b max [J k represents the eigenvector corresponding to the maximum eigenvalue of the interference matrix J k , P k represents the projection matrix of the receiving end k, I Nk represents the identity matrix of size N k ; S14. Set the interference leakage threshold, calculate the total interference leakage of the interference alignment system according to the orthonormal basis, and judge whether it is greater than the interference leakage threshold. If so, execute step S15, otherwise output the transmit beamforming vectors, receive beamforming vectors, and artificial noise unit precoding matrices between all legitimate transceivers; The calculation formula for the total interference leakage of the interference alignment system is: Among them, H ki represents the channel matrix from the transmitter i to the receiver k, and v i represents the transmit beamforming vector of the transmitter i, and C k represents a set of orthonormal bases of the receiver k, and L k represents the interference leakage of the receiver k; S15. Calculate the transmit beamforming vector of the corresponding transmitter through the projection matrix and obtain the artificial noise unit precoding matrix; The calculation process of step S15 is as follows: S21. Update the interference matrix of the corresponding transmitter through the projection matrix of the receiver; S22. Update the transmit beamforming vector of the corresponding transmitter according to the updated interference matrix; S23. After the update is completed, the receiver r calculates the artificial noise interference matrix through its updated receive beamforming vector; S24. Calculate a new artificial noise unit precoding matrix according to the artificial noise interference matrix; S16. After the calculation is completed, judge whether the maximum number of iterations is reached. If so, output the transmit beamforming vectors, receive beamforming vectors, and artificial noise unit precoding matrices between all legitimate transceivers. Otherwise, add 1 to the number of iterations and return to step S12; S3. After interference alignment, calculate the signal-to-noise ratio of the receiver r and the signal-to-noise ratio of the T eavesdropping nodes, and construct an objective function for optimizing the power allocation coefficient and the security outage probability of the transmitter r; The objective function is expressed as: Among them, the constraint conditions of the objective function are R th represents the minimum security rate of the receiving end r, represents the power coefficient allocated by the sending end r to the useful signal, ε represents the security outage probability, R s is the security rate of the receiving end r, represents the capacity of the main channel at the receiving end r, represents the signal-to-noise ratio at the t-th single-antenna eavesdropping node; The signal-to-noise ratio at the $t$-th single-antenna eavesdropping node is expressed as: Among them, M r represents the number of antennas of the transmitting end r, h t,r represents the channel vector from the transmitting end r to the single-antenna eavesdropping node t, v r represents the transmit beamforming vector of the transmitting end r, V [an]r represents the artificial noise unit precoding matrix transmitted by the transmitting end r, P represents the transmit power of the remaining transmitting ends, P r represents the transmit power of the transmitting end r; S4. Analyze the objective function by numerical methods to obtain the optimal power allocation coefficient and achieve secure transmission of the wireless interference network under the optimal security outage probability.

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