MISO-oriented covert communication optimization method and system

Abstract

The invention discloses an MISO-oriented covert communication optimization method and system, and the method comprises the following steps: (1) constructing an MISO-oriented covert communication system model which comprises a transmitter with multiple antennas, a receiver with receiving and interference functions, and a listener; (2) constructing an optimization problem of the MISO-oriented covert communication; (3) converting the optimization problem into a convex optimization problem; and (4) carrying out iterative solution on the convex optimization problem until values of Pa, ua and ub when the value of the average covert rate R is maximum are obtained, and outputting the values as an optimal covert communication strategy. According to the invention, high concealment and high communication rate are realized at the same time.

Description

Technical Field

[0001] The present invention relates to covert communication technology, and in particular to a covert communication optimization method and system oriented to MISO (multiple input single output). Background Art

[0002] With the widespread application of wireless communications, communication security issues have received increasing attention due to the broadcast characteristics of wireless channels. Most existing secure transmission technologies focus on protecting content from eavesdropping, such as encryption technology and physical layer security technology, but with the continuous development of eavesdropping technology, this protection measure is becoming increasingly insufficient. Relying solely on encryption to ensure the security of information content may not be able to effectively prevent advanced attack methods, such as traffic analysis and side channel attacks. Therefore, future security technologies should incorporate more comprehensive protection mechanisms, not only to ensure the confidentiality of information content, but also to pay attention to the integrity and authenticity of data and various security threats that may be encountered during transmission, so as to achieve information protection. An emerging technology is dedicated to concealing information content, that is, making it impossible for the listener to determine whether the monitored target has transmitted information. This technology is covert communication.

[0003] Covert communication technology aims to establish a communication link with a low probability of being discovered, providing strong security for communication, but its feasibility is limited by the high detectability of eavesdroppers. In addition, the high-power transmission performed by legitimate users to achieve high data rate communication can easily lead to signal transmission exposure. Therefore, how to achieve high concealment and high communication rate at the same time in the presence of eavesdroppers has become the biggest challenge of covert communication. Summary of the invention

[0004] In view of the problems existing in the prior art, the object of the present invention is to provide a MISO-oriented covert communication optimization method and system that can achieve both high concealment and high communication rate.

[0005] In order to achieve the above-mentioned object of the invention, the present invention provides the following technical solutions: A covert communication optimization method for MISO includes the following steps: (1) Constructing a covert communication system model for MISO, the covert communication system model includes a transmitter with multiple antennas, a receiver with both receiving and jamming functions, and an eavesdropper; (2) The optimization problem for constructing covert communication for MISO is: , In the formula, represents the average concealment rate, and the subscripts a, b, and w represent the transmitter, receiver, and listener, respectively. Indicates the transmission power of the transmitter. are the simulated beamforming vectors for the transmitter and receiver, respectively, is the power of the interference signal transmitted by the receiver, represents the noise variance, represents the channel coefficient vector of the link between the transmitter and the receiver, represents the channel coefficient vector of the receiver's self-interference channel, Express about and Find the expectation of the function, represents the probability of detection error of the listener, Express about and Find the expectation of the function, represents the minimum required probability that the listener makes an inaccurate decision, express The kth element of express The mth element of Indicates the number of transmitting antennas of the transmitter, Indicates the number of receiver transmit antennas, Indicates the maximum transmission power of the transmitter, the superscript H represents the conjugate transpose, represents the channel coefficient vector of the link between the transmitter and the listener, A vector of channel coefficients representing the link between the receiver and the listener; (3) transforming the optimization problem into a convex optimization problem; (4) Iterate the convex optimization problem until the maximum average concealment rate is obtained. The value of is output as the optimal strategy for covert communication.

[0006] A covert communication optimization system for MISO, comprising: A communication model building module, used to build a covert communication system model for MISO, wherein the covert communication system model includes a transmitter with multiple antennas, a receiver with both receiving and interference functions, and an eavesdropper; The optimization problem building module used to construct the optimization problem for covert communication for MISO is: , In the formula, represents the average concealment rate, and the subscripts a, b, and w represent the transmitter, receiver, and listener, respectively. Indicates the transmission power of the transmitter. are the simulated beamforming vectors for the transmitter and receiver, respectively, is the power of the interference signal transmitted by the receiver, represents the noise variance, represents the channel coefficient vector of the link between the transmitter and the receiver, represents the channel coefficient vector of the receiver's self-interference channel, Express about and Find the expectation of the function, represents the probability of detection error of the listener, Express about and Find the expectation of the function, represents the minimum required probability that the listener makes an inaccurate decision, express The kth element of express The mth element of Indicates the number of transmitting antennas of the transmitter, Indicates the number of receiver transmit antennas, Indicates the maximum transmission power of the transmitter, the superscript H represents the conjugate transpose, represents the channel coefficient vector of the link between the transmitter and the listener, A vector of channel coefficients representing the link between the receiver and the listener; A problem conversion module, used for converting the optimization problem into a convex optimization problem; The problem solving module is used to iteratively solve the convex optimization problem until the maximum average concealment rate value is obtained. The value of is output as the optimal strategy for covert communication.

[0007] Compared with the prior art, the present invention has the following beneficial effects: under certain concealment constraints, the present invention designs analog beamforming vectors and transmit signal power, while taking into account the unit modulus constraints and transmit power constraints of the analog beamformer, thereby maximizing the communication rate between two legitimate users. This method comprehensively considers channel conditions, interference environment, and user needs, and strives to improve the communication rate between legitimate communication users without significantly increasing the detectable signal characteristics, so as to achieve efficient and undetectable wireless communication. In addition, compared with existing work, the present invention fills the research gap in interference-assisted full-duplex covert millimeter wave communication. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 It is a flowchart of a covert communication optimization method for MISO provided by an embodiment of the present invention; Figure 2 is an architectural diagram of a covert communication system model in an embodiment of the present invention; Figure 3It is a schematic diagram of the solution process of the convex optimization problem in an embodiment of the present invention. DETAILED DESCRIPTION

[0009] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0010] The embodiment of the present invention provides a covert communication optimization method for MISO, such as Figure 1 As shown, the following steps are included: (1) Construct a covert communication system model for MISO.

[0011] The covert communication system model includes a transmitter with multiple antennas, a receiver with both receiving and interference functions, and an eavesdropper. Figure 2 As shown in the figure, assume that the transmitter is Alice, the receiver is Bob, and the listener is Willie. Bob receives the signal transmitted by Alice while sending interference signals to affect Willie's monitoring. Alice is equipped with multiple antennas for transmitting signals, Bob is equipped with a single antenna for receiving signals and multiple antennas for transmitting interference signals, and Willie is equipped with one antenna to monitor whether Alice is transmitting signals.

[0012] This embodiment selects a widely used cluster channel model to construct the channel model between Alice, Bob, and Willie, and the self-interference channel model of Bob is as follows: make , They represent the channel coefficient vectors of Alice-to-Bob link, Alice-to-Willie link, Bob-to-Willie link, and Bob self-interference channel, respectively, where represents the number of Alice's transmitting antennas, represents the number of Bob's transmitting antennas, express is The complex vector of , , Similarly, the channel model is established according to the 3GPP / ITU model as follows: , Subscript , represents the channel coefficient vector of the link between x and y, represents the number of sub-paths of the link between x and y, represents the average path loss of the link between x and y, represents the number of antennas of x, Indicates the link between x and y The small-scale channel gain of the sliver path, , represents the normalized sth response vector, and , represents the transmission angle of the signal transmitter of the sth subpath of the link between x and y, , , represents the antenna spacing, represents the carrier wavelength, express Any value in represents the number of transmitting antennas at the transmitting end of the link between x and y. To simplify the following discussion, let .

[0013] The above cluster channel model is a far-field channel model, that is, the receiving end regards the signal as a plane wave, which is usually not applicable to the self-interference channel because the distance between the transmitting antenna and the receiving antenna of the self-interference end is small compared with the wavelength of the carrier, which does not meet the conditions of the far-field model. (D is the distance between the transmitting antenna array and the receiving antenna array). The self-interference channel model used in this embodiment is: ,in is the Rice factor, Represent the line-of-sight component and non-line-of-sight component of the self-interference channel respectively. Since the transmission distance of the non-line-of-sight link is usually longer than the transmission distance of the wavelength, the above far-field model ( ) to model The model of the sight distance component is as follows: , in, Represents the nth element of the sight distance component, To ensure The power normalization constant called, It means to find the average value, is the distance between Bob's nth transmitting antenna and Bob's receiving antenna, as follows: , is the wavelength and θ is the angle between the arrays.

[0014] It is understandable that in other embodiments, other methods may be used to construct the channel model, such as a Rayleigh channel model, a Gaussian channel model, etc.

[0015] (2) Construct the optimization problem of covert communication for MISO.

[0016] According to the channel model, if Alice transmits a signal , Bob transmits a jamming signal , then the signal sequence received by Bob is for: ,in is the signal index, N is the number of signals, is the channel noise between Alice and Bob, represents the noise variance, and the subscripts a, b, and w represent the transmitter, receiver, and listener, respectively. represents Alice’s transmit power, are the simulated beamforming vectors for Alice and Bob, is the power of the interference signal transmitted by Bob. , , Obey 0 to The randomness of Bob's transmission power is introduced in this embodiment to make Willie unable to determine whether the fluctuation of his received signal is caused by Alice's transmission or Bob's interference, thereby increasing the probability of detection error at Willie's end. and Take the average to get the average concealment rate The calculation formula is: , The process of solving the minimum probability of Willie making an incorrect decision is as follows: Willie's signal detection can be classified as a binary hypothesis testing problem. Let the null hypothesis H0 mean that Alice remains silent, that is, does not transmit a signal, and the alternative hypothesis H1 means that Alice transmits an information signal. In the two cases, the signals received by Willie are: , , in, represents the channel noise between Alice and Willie. Assume that Willie uses a radiometer as its detector for energy detection to detect Alice's activities, and Willie observes an infinite number of channel uses, which represents the worst case for communication concealment. In this case, Willie performs a likelihood ratio test to detect the presence of Alice's signal transmission, which is given by the formula , D0 represents the detection performed when Willie believes that Alice has not transmitted a signal, and D1 represents the detection performed when Willie believes that Alice has transmitted a signal. represents the predetermined detection threshold used by Willie, Represents statistical data, and its expression is: .

[0017] Because Willie received the The introduced energy is random, and Willie will make mistakes in signal detection, including missed detection (MD) and false alarm (FA). A missed detection event is defined as Willie performing detection D0 but H1 is true, and the corresponding probability is The false alarm event is defined as Willie performing detection D1 but H0 is true, and the corresponding probability is Assume that Willie has no information about when Alice transmits, so his best guess is to assume and The prior probabilities of are considered equal, which leads to The probability of Willie's detection error is defined as: , in, , , and They represent the energy of the signal sent by the receiver and the transmitter reaching the listener. , The statistical channel information of , The average minimum detection error probability is taken to evaluate the concealment of communication, that is, , in Express , Take the average minimum detection error probability, , , is the intermediate variable, , Respectively and The covariance matrix of the complex Gaussian distribution.

[0018] The optimization problem for constructing covert communication for MISO is: , In the formula, Express about and Find the expectation of the function, Express about and Find the expectation of the function, represents the minimum required probability that the listener makes an inaccurate decision, express The kth element of express The mth element of H represents the conjugate transpose.

[0019] (3) Convert the optimization problem into a convex optimization problem.

[0020] When transforming the problem, we first transform the objective function and constraints of the optimization problem of covert communication for MISO into easy-to-handle formulas. and The coupling between them is difficult to obtain As an alternative, a widely used lower bound optimization method is used to convert Replace it with its lower limit and optimize the lower limit to indirectly maximize the concealment rate. Through Jensen's inequality, , in, express The lower bound of is an auxiliary variable, represents the normalized 1st,…, response vector, represents the receiver self-interference channel No. 1,…, The emission angle of the signal transmitting end of the strip path, Represents the number of receiver self-interference channel subpaths.

[0021] Then by introducing auxiliary variables and , can be rewritten as: , In the formula, express The conjugate of The function after the average concealment rate R is replaced by the lower bound optimization method, Re() represents the real part. Compare With more optimization variables, but The formula of helps to implement the inexact block coordinate descent (IBCD) algorithm because is a convex function of the remaining variable while keeping all other four variables fixed.

[0022] For hidden constraints ,because About The increasing function of can be rewritten as , Determine by bisection search, that is, when hour, The hidden constraint can be expressed as: , Then, through the first-order Taylor expansion, we can use its first-order Taylor expansion to replace the non-convex part on the right side of the formula, thus obtaining: , in, Respectively represent the ) iterations , The optimal solution of .

[0023] For the unit module constraint, it is transformed into: , in, , are auxiliary variables, express The element in the i-th row and i-th column of express The element at row j and column j, Indicates seeking trace.

[0024] against , The two non-convex terms also use the same first-order Taylor expansion, then: , , Thus, the optimization problem is transformed into the following convex optimization problem: , , , , .

[0025] It is understandable that in other embodiments, the optimization problem can also be transformed into other forms of convex optimization problems by means of the variable lower bound method and the introduction of auxiliary variables. As long as it is a solvable convex optimization problem, it can be used.

[0026] (4) Iteratively solve the convex optimization problem until the average concealment rate is obtained. When the value is maximum The value of is output as the optimal strategy for covert communication.

[0027] like Figure 3 As shown in Figure 2, the solution process specifically includes: (4.1) Settings Initial value of , set the number of iterations l =1; (4.2) Fixed , solve the problem ,get The optimal solution : , (4.3) Based on the optimal solution ,fixed , solve the problem ,get The optimal solution : , (4.4) Updated to ,Will Updated to , and use the successive convex approximation method to solve the problem , get the current iteration time , The value of , , ; (4.5) Determine whether the average concealment rate difference reaches the preset threshold. If so, execute (4.6). Otherwise, l = l +1, return to execution (4.2); (4.6) At this time , The value of is output as the optimal strategy for covert communication.

[0028] It is understandable that the solution process can also be other ways, such as first fixing the solution , and then solve , and then solve , The optimal strategy can be obtained by using an iterative loop or other iterative loops.

[0029] The embodiment of the present invention further provides a MISO-oriented covert communication optimization system, including: A communication model building module, used to build a covert communication system model for MISO, wherein the covert communication system model includes a transmitter with multiple antennas, a receiver with both receiving and interference functions, and an eavesdropper; The optimization problem building module used to construct the optimization problem for covert communication for MISO is: , In the formula, represents the average concealment rate, and the subscripts a, b, and w represent the transmitter, receiver, and listener, respectively. Indicates the transmission power of the transmitter. are the simulated beamforming vectors for the transmitter and receiver, respectively, is the power of the interference signal transmitted by the receiver, represents the noise variance, represents the channel coefficient vector of the link between the transmitter and the receiver, represents the channel coefficient vector of the receiver's self-interference channel, Express about and Find the expectation of the function, represents the probability of detection error of the listener, Express about and Find the expectation of the function, represents the minimum required probability that the listener makes an inaccurate decision, express The kth element of express The mth element of Indicates the number of transmitting antennas of the transmitter, Indicates the number of receiver transmit antennas, Indicates the maximum transmission power of the transmitter, the superscript H represents the conjugate transpose, represents the channel coefficient vector of the link between the transmitter and the listener, A vector of channel coefficients representing the link between the receiver and the listener; A problem conversion module, used for converting the optimization problem into a convex optimization problem; The problem solving module is used to iteratively solve the convex optimization problem until the maximum average concealment rate value is obtained. The value of is output as the optimal strategy for covert communication.

[0030] The detection error probability of the listener is specifically: , In the formula, Indicates the maximum transmission power of the receiver transmitting the interference signal, , , and They represent the energy of the signals sent by the receiver and transmitter reaching the listener.

[0031] The convex optimization problem is specifically: , , , , , In the formula, is the function after the average concealment rate R is replaced by the lower bound optimization method, and is the auxiliary variable introduced during conversion. express The conjugate of , Re() means taking the real part, Indicates the maximum transmission power of the interference signal transmitted by the receiver; represents the Rice factor, represents the line-of-sight component of the receiver's self-interference channel, and , represents the non-line-of-sight component of the receiver’s self-interference channel, represents auxiliary variables, represents the normalized 1st,…, response vector, represents the receiver self-interference channel No. 1,…, The emission angle of the signal transmitting end of the strip path, represents the number of receiver self-interference channel subpaths; , Respectively and The covariance matrix of the complex Gaussian distribution is, Express satisfaction of The conversion value of , is the intermediate variable, Respectively represent the ) iterations , The optimal solution of , are auxiliary variables, express The element in the i-th row and i-th column of express The element at row j and column j, Indicates seeking trace.

[0032] The problem-solving module specifically includes: Initial value setting unit, used to set Initial value of , set the number of iterations l =1; The first problem solving unit is used to fix , solve the problem ,get The optimal solution : , The second problem solving unit is used to solve the problem based on the optimal solution. ,fixed , solve the problem ,get The optimal solution : , The third problem solving unit is used to Updated to ,Will Updated to , and use the successive convex approximation method to solve the problem , get the current iteration time , The value of , , ; The cut-off judgment unit is used to judge whether the average concealment rate difference reaches a preset threshold. If so, the strategy output unit is executed, otherwise l = l +1, return to execute the first problem solving unit; The strategy output unit is used to output the , The value of is output as the optimal strategy for covert communication.

[0033] Wherein, the channel model of the MISO-oriented covert communication system model is: , Subscript , represents the channel coefficient vector of the link between x and y, represents the number of sub-paths of the link between x and y, represents the average path loss of the link between x and y, represents the number of antennas of x, Indicates the link between x and y The small-scale channel gain of the sliver path, , represents the normalized sth response vector, and , represents the transmission angle of the signal transmitter of the sth subpath of the link between x and y, , , represents the antenna spacing, represents the carrier wavelength, express Any value in Represents the number of transmit antennas at the transmitting end of the link between x and y.

[0034] The system provided in the embodiment of the present invention can be used to execute the method provided in the first embodiment of the present invention, and has the corresponding functions and beneficial effects of executing the method. The similarities are referred to the method description and will not be repeated here.

[0035] It is worth noting that in the embodiment of the above system, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0036] The embodiments described above are only illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, i.e., they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, or of course, it can be implemented only by hardware, as long as the function or effect can be achieved.

[0037] It should be understood that the above embodiments and descriptions only describe the principles, main features and advantages of the present invention. Without departing from the spirit and scope of the present invention, the present invention may be subject to various changes and improvements, and these changes and improvements all fall within the scope of protection of the present invention.

Claims

1. A covert communication optimization method for MISO, characterized in that: The steps include: (1) Constructing a covert communication system model for MISO, the covert communication system model includes a transmitter with multiple antennas, a receiver with both receiving and jamming functions, and an eavesdropper; (2) The optimization problem for constructing covert communication for MISO is: , In the formula, represents the average concealment rate, and the subscripts a, b, and w represent the transmitter, receiver, and listener, respectively. Indicates the transmission power of the transmitter. are the simulated beamforming vectors for the transmitter and receiver, respectively, is the power of the interference signal transmitted by the receiver, represents the noise variance, represents the channel coefficient vector of the link between the transmitter and the receiver, represents the channel coefficient vector of the receiver's self-interference channel, Express about and Find the expectation of the function, represents the probability of detection error of the listener, Express about and Find the expectation of the function, represents the minimum required probability that the listener makes an inaccurate decision, express The kth element of express The mth element of Indicates the number of transmitting antennas of the transmitter, Indicates the number of receiver transmit antennas, Indicates the maximum transmission power of the transmitter, the superscript H represents the conjugate transpose, represents the channel coefficient vector of the link between the transmitter and the listener, A vector of channel coefficients representing the link between the receiver and the listener; (3) transforming the optimization problem into a convex optimization problem; (4) Iterate the convex optimization problem until the maximum average concealment rate is obtained. The value of is output as the optimal strategy for covert communication.

2. The MISO-oriented covert communication optimization method according to claim 1, characterized in that: The detection error probability of the listener is specifically: , In the formula, represents the probability of detection error of the listener, Indicates the maximum transmission power of the receiver transmitting the interference signal, , , and They represent the energy of the signals sent by the receiver and transmitter reaching the listener.

3. The MISO-oriented covert communication optimization method according to claim 1, characterized in that: The convex optimization problem in step (3) is specifically: , , , , , In the formula, is the function after the average concealment rate R is replaced by the lower bound optimization method, and is the auxiliary variable introduced during conversion. express The conjugate of , Re() means taking the real part, Indicates the maximum transmission power of the interference signal transmitted by the receiver; represents the Rice factor, represents the line-of-sight component of the receiver's self-interference channel, and , represents the non-line-of-sight component of the receiver’s self-interference channel, represents auxiliary variables, represents the normalized 1st,…, response vector, represents the receiver self-interference channel No. 1,…, The emission angle of the signal transmitting end of the strip path, represents the number of receiver self-interference channel subpaths; , Respectively and The covariance matrix of the complex Gaussian distribution is, Express satisfaction of The conversion value of , , , is the intermediate variable, Respectively represent the ) iterations , The optimal solution of , are auxiliary variables, express The element in the i-th row and i-th column of express The element at row j and column j, Indicates seeking trace.

4. The MISO-oriented covert communication optimization method according to claim 3, characterized in that: Step (4) specifically includes: (4.1) Settings Initial value of , set the number of iterations l =1; (4.2) Fixed , solve the problem ,get The optimal solution : , (4.3) Based on the optimal solution ,fixed , solve the problem ,get The optimal solution : , (4.4) Updated to ,Will Updated to , and use the successive convex approximation method to solve the problem , get the current iteration time , The value of , , ; (4.5) Determine whether the average concealment rate difference reaches the preset threshold. If so, execute (4.6). Otherwise, l = l +1, return to execution (4.2); (4.6) At this time , The value of is output as the optimal strategy for covert communication.

5. The MISO-oriented covert communication optimization method according to claim 1, characterized in that: The channel model of the MISO-oriented covert communication system model is: , Subscript , represents the channel coefficient vector of the link between x and y, represents the number of sub-paths of the link between x and y, represents the average path loss of the link between x and y, represents the number of antennas of x, Indicates the link between x and y The small-scale channel gain of the sliver path, , represents the normalized sth response vector, and , represents the transmission angle of the signal transmitter of the sth subpath of the link between x and y, , , represents the antenna spacing, represents the carrier wavelength, express Any value in Represents the number of transmit antennas at the transmitting end of the link between x and y.

6. A covert communication optimization system for MISO, characterized in that: include: A communication model building module, used to build a covert communication system model for MISO, wherein the covert communication system model includes a transmitter with multiple antennas, a receiver with both receiving and interference functions, and an eavesdropper; The optimization problem building module used to construct the optimization problem for covert communication for MISO is: , In the formula, represents the average concealment rate, and the subscripts a, b, and w represent the transmitter, receiver, and listener, respectively. Indicates the transmission power of the transmitter. are the simulated beamforming vectors for the transmitter and receiver, respectively, is the power of the interference signal transmitted by the receiver, represents the noise variance, represents the channel coefficient vector of the link between the transmitter and the receiver, represents the channel coefficient vector of the receiver's self-interference channel, Express about and Find the expectation of the function, represents the probability of detection error of the listener, Express about and Find the expectation of the function, represents the minimum required probability that the listener makes an inaccurate decision, express The kth element of express The mth element of Indicates the number of transmitting antennas of the transmitter, Indicates the number of receiver transmit antennas, Indicates the maximum transmission power of the transmitter, the superscript H represents the conjugate transpose, represents the channel coefficient vector of the link between the transmitter and the listener, A vector of channel coefficients representing the link between the receiver and the listener; A problem conversion module, used for converting the optimization problem into a convex optimization problem; The problem solving module is used to iteratively solve the convex optimization problem until the maximum average concealment rate value is obtained. The value of is output as the optimal strategy for covert communication.

7. The MISO-oriented covert communication optimization system according to claim 6, characterized in that: The detection error probability of the listener is specifically: , In the formula, represents the probability of detection error of the listener, Indicates the maximum transmission power of the receiver transmitting the interference signal, , , and They represent the energy of the signals sent by the receiver and transmitter reaching the listener.

8. The MISO-oriented covert communication optimization system according to claim 6, characterized in that: The convex optimization problem is specifically: , , , , , In the formula, is the function after the average concealment rate R is replaced by the lower bound optimization method, and is the auxiliary variable introduced during conversion. express The conjugate of , Re() means taking the real part, Indicates the maximum transmission power of the interference signal transmitted by the receiver; represents the Rice factor, represents the line-of-sight component of the receiver's self-interference channel, and , represents the non-line-of-sight component of the receiver’s self-interference channel, represents auxiliary variables, represents the normalized 1st,…, response vector, represents the receiver self-interference channel No. 1,…, The emission angle of the signal transmitting end of the strip path, represents the number of receiver self-interference channel subpaths; , Respectively and The covariance matrix of the complex Gaussian distribution is, Express satisfaction of The conversion value of , , , is the intermediate variable, Respectively represent the ) iterations , The optimal solution of , are auxiliary variables, express The element in the i-th row and i-th column of express The element at row j and column j, Indicates seeking trace.

9. The MISO-oriented covert communication optimization system according to claim 8, characterized in that: The problem-solving module specifically includes: Initial value setting unit, used to set Initial value of , set the number of iterations l =1; The first problem solving unit is used to fix , solve the problem ,get The optimal solution : , The second problem solving unit is used to solve the problem based on the optimal solution. ,fixed , solve the problem ,get The optimal solution : , The third problem solving unit is used to Updated to ,Will Updated to , and use the successive convex approximation method to solve the problem , get the current iteration time , The value of , , ; The cut-off judgment unit is used to judge whether the average concealment rate difference reaches a preset threshold. If so, the strategy output unit is executed, otherwise l = l +1, return to execute the first problem solving unit; The strategy output unit is used to output the , The value of is output as the optimal strategy for covert communication.

10. The MISO-oriented covert communication optimization system according to claim 6, characterized in that: The channel model of the MISO-oriented covert communication system model is: , Subscript , represents the channel coefficient vector of the link between x and y, represents the number of sub-paths of the link between x and y, represents the average path loss of the link between x and y, represents the number of antennas of x, Indicates the link between x and y The small-scale channel gain of the sliver path, , represents the normalized sth response vector, and , represents the transmission angle of the signal transmitter of the sth subpath of the link between x and y, , , represents the antenna spacing, represents the carrier wavelength, express Any value in Represents the number of transmit antennas at the transmitting end of the link between x and y.

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