NOMA-assisted security beam forming method with multicast and unicast communication perception integration

Abstract

The invention discloses a security beam forming method with integration of multicast and unicast communication perception assisted by NOMA, and the method comprises the steps: a base station sends a multicast and unicast mixed signal to a communication user and a radar user, a potential eavesdropper eavesdrops the unicast signal, and the base station carries out the perception of the radar user and a target through the sent mixed signal, after the mixed signal is reflected by a radar user and a target, the base station receives a radar echo signal, and a communication user decodes a multicast signal by using NOMA (Non-Orthogonal Multiple Access) and eliminates interference of the multicast signal on a unicast signal by using an interference elimination technology of the NOMA; establishing a power minimization optimization problem under the conditions that the communication performance of a user and the perception performance of a radar user and a target are met and the unicast eavesdropping performance is inhibited; for the problem, discrete relaxation is carried out on an existing area of the target, an S-lemma is used for substituting channel estimation errors, the problem is converted into a convex optimization problem through SDR, and then a convex optimization solver is used for obtaining multicast and unicast beams; the method has the advantages of low power consumption and good robustness.

Description

Technical Field

[0001] The present invention relates to a beamforming technology of an ISAC (Integrated Sensing and Communication) system, and in particular to a NOMA (Non-Orthogonal Multiple Access) assisted secure beamforming method with integrated multicast and unicast communication perception. Background Art

[0002] With the rapid development of wireless communication technology, the number of IoT devices has exploded, and the shortage of spectrum resources has become an urgent problem to be solved in the field of wireless communication. At the same time, with the development of emerging technologies such as smart cities, smart industries, Internet of Vehicles, and telemedicine, wireless communication systems are required to have not only efficient and reliable data transmission capabilities, but also real-time and accurate perception capabilities. However, traditional communication and perception systems are often designed and operated independently, which leads to some waste of spectrum resources and increased hardware costs.

[0003] In this context, ISAC technology came into being. ISAC technology aims to integrate the two functions of communication and perception, and realize the collaborative work of communication and perception functions by sharing spectrum resources and hardware platforms. By sharing spectrum resources, ISAC technology enables the system to use the same frequency band for data transmission and perception tasks at the same time, thereby improving the utilization of the spectrum. In addition, by sharing the hardware platform between communication and perception, ISAC technology reduces the cost of equipment and the waste of hardware resources. In summary, ISAC technology solves the problems of tight spectrum resources, high hardware costs, and limited system performance by deeply integrating communication and perception functions, providing new ideas and directions for the development of wireless communication technology.

[0004] However, with the widespread application of ISAC technology, the security challenges it faces are becoming increasingly prominent. Due to the openness of wireless communication channels, signals are susceptible to various interferences and attacks during transmission, such as eavesdropping, interference, and deception. These interferences and attacks will seriously affect the communication quality and perception performance of the ISAC system, and even directly affect the stability and reliability of the entire system. However, in existing research on the physical layer security of ISAC, the objects of communication and perception are often separated, and the integration of communication and perception has not been truly realized. In addition, the security beam design in the ISAC system often requires the base station to send additional artificial noise to interfere with the eavesdropper. Since artificial noise does not carry any useful information, this will cause unnecessary power consumption. In addition, in practical applications, it is difficult to obtain perfect communication channel state information, and it is necessary to consider the robustness of the system in the presence of errors in the communication channel. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a NOMA-assisted secure beamforming method with integrated multicast and unicast communication perception, which regards radar users as both perceived objects and objects communicating with dual-function base stations, integrates communication and perception together, truly realizes communication and perception integration, and uses multicast signals instead of artificial noise that does not carry any information to prevent unicast signals from being eavesdropped by radar targets that are potential eavesdroppers, saving unnecessary power loss. It introduces bounded errors in the channel from the dual-function base station to the communication user, and considers the existence area of ​​the radar target as a continuous angle area instead of a fixed point, thereby improving the robustness of the communication and perception integration system.

[0006] The technical solution adopted by the present invention to solve the above technical problems is: a NOMA-assisted secure beamforming method with integrated multicast and unicast communication perception, characterized in that it includes the following steps:

[0007] Step 1: For the integrated communication and perception system, an ISAC multicast and unicast communication model is constructed. The model includes a dual-function base station, two users, and a radar target. The dual-function base station is configured with a uniform linear array. The dual-function base station is used to perform communication and perception tasks. The two users are a communication user and a radar user. The communication user only needs to communicate with the dual-function base station. The radar user needs to communicate with the dual-function base station and be perceived by the dual-function base station. The communication intensity between the communication user and the dual-function base station is higher than the communication intensity between the radar user and the dual-function base station. The radar target will also act as a potential eavesdropper to eavesdrop on the private communication between the dual-function base station and the user.

[0008] Step 2: The dual-function base station simultaneously sends a multicast-unicast mixed signal to the communication user and the radar user. The radar target, which is a potential eavesdropper, eavesdrops on the unicast signal. At the same time, the dual-function base station uses the sent multicast-unicast mixed signal to sense the radar user and the radar target. The multicast-unicast mixed signal is reflected by the radar user and the radar target respectively, and the dual-function base station receives the radar echo signal. The multicast-unicast mixed signal x sent by the dual-function base station is expressed as x=w m s m +w u s u , the signal y received by the communication user c Expressed as The signal y received by the radar user r Expressed as The signal y that is intercepted by the radar target as a potential eavesdropper t Expressed as The radar echo signal y received by the dual-function base stationBS Represented as y BS =ζ t αa(θ t ) H (θ t )x+ζ r βa(θ r ) H (θ r )x+n; wherein the power of the multicast signal in the multicast-unicast mixed signal is greater than the power of the unicast signal, w m s m represents the multicast signal in x, s m represents the symbol carrying multicast information, w m Indicates m The beamforming vector, w u s u represents a unicast signal in x, s u represents the unicast information bearing symbol, w u Indicates u The beamforming vector, s m and u All have unit power and are independent of each other, h c represents the channel from the dual-function base station to the communication user, () H is the conjugate transpose operation, n c represents the additive Gaussian white noise received by the communication user, n c The variance of represents the channel from the dual-function base station to the radar user, β represents the path loss from the dual-function base station to the radar user, and θ r represents the azimuth from the dual-function base station to the radar user, a(θ r ) represents the radar user's steering vector, e is a natural constant, j is an imaginary unit, d is the antenna spacing of the uniform linear array configured for the dual-function base station, λ is the carrier wavelength, N is the number of antennas of the uniform linear array configured for the dual-function base station, () T is the transpose operation, n r represents the additive white Gaussian noise received by the radar user, n r The variance of represents the channel from the dual-function base station to the radar target as a potential eavesdropper, α represents the path loss from the dual-function base station to the radar target as a potential eavesdropper, and θ t represents the azimuth from the dual-function base station to the radar target as a potential eavesdropper, a(θ t ) represents the guidance vector of the radar target as a potential eavesdropper, n trepresents the additive white Gaussian noise received at the radar target as a potential eavesdropper, n t The variance of ζ t represents the reflection coefficient of the radar target, ζ r represents the reflection coefficient of the radar user, and n represents y BS The noise of n is σ 2 ;

[0009] Step 3: Under the premise that the communication user needs both multicast and unicast signals, and the power of the multicast signal is greater than the power of the unicast signal, the communication user uses NOMA to first decode the multicast signal, and uses NOMA's interference cancellation technology to eliminate the interference caused by the multicast signal to the unicast signal, and increases the SINR of the multicast signal received at the communication user. c,m Expressed as The SINR of the unicast signal received at the communication user c,u Expressed as Under the premise that the radar user only needs the multicast signal, the multicast signal receiving signal to noise ratio SINR at the radar user is calculated. r,m Expressed as Under the premise that the radar target as a potential eavesdropper does not know the decoding order of the communication user using NOMA decoding, the unicast signal receiving signal to noise ratio SINR at the radar target as a potential eavesdropper is calculated. t,u Expressed as The weight vector u of the radar target t and the radar user's steering vector a(θ r ) are orthogonal, the weight vector u of the radar user r and the guidance vector a(θ t ) are orthogonal, the output signal to interference and noise ratio SINR of the radar target at the dual-function base station is BS,t , The output signal to interference and noise ratio SINR of the radar user at the dual-function base station BS,r , Then the multicast signal communication rate R at the communication user c,m Expressed as The unicast signal communication rate R at the communication user c,u Expressed as The multicast signal communication rate R at the radar user r,m Expressed as The eavesdropping rate R of the unicast signal at the radar target as a potential eavesdropper t,u , Among them, || is the modulo operator, Tr() means finding the trace of the matrix, represents the covariance matrix of the multicast and unicast mixed signal x, A(θ t ) and A(θ r ) are introduced as intermediate quantities, A(θ t )=a(θ t ) H (θ t ), A(θ r )=a(θ r ) H (θ r );

[0010] Step 4: Under the conditions of satisfying the multicast and unicast hybrid communication performance of communication users and radar users, the perception performance of radar users and radar targets, and suppressing the unicast eavesdropping performance of radar targets as potential eavesdroppers, a power minimization optimization problem is established, which is described as:

[0011]

[0012] Among them, p t is the objective function of the power minimization optimization problem, p t Indicates the transmit power of a dual-function base station,

[0013] η u represents the unicast signal communication rate threshold, η m represents the multicast signal communication rate threshold, η t represents the unicast signal eavesdropping rate threshold, γ t represents the radar target output signal-to-interference-noise ratio threshold, γ r represents the radar user output signal-to-interference-noise ratio threshold, Θ t Indicates the existence area of ​​the radar target, which is a continuous angle area. represents the channel estimation value from the dual-function base station to the communication user, δ c represents the channel estimation error from the dual-function base station to the communication user, which is a bounded error, δ c Satisfy the condition ||δ c ||2≤∈ c ,||||2 is the binary norm operator,∈ c is the threshold value;

[0014] Step 5: For the power minimization optimization problem established in step 4, t Discretize and relax, and use the S-lemma to introduce δ c , rewrite constraint C1 into semi-positive definite matrix form Rewrite constraint C2 into semi-positive matrix form Then, we use the semi-positive definite relaxation technique to convert Θ tThe power minimization optimization problem after discretization relaxation and rewriting of constraints C1 and C2 is converted into a convex optimization problem; then the convex optimization problem is solved using a convex optimization solver to obtain w u and w m Their respective solutions; among them, G u and G m is the intermediate quantity introduced, r u and r m is the intermediate quantity introduced, λ u and λ m is the non-negative auxiliary variable introduced, I N Represents the identity matrix of order N.

[0015] In step 2, h c Modeled as the Rice channel model, Where k is the Rice factor, h los represents the line-of-sight link from the dual-function base station to the communication user, h nlos represents the non-line-of-sight link from the dual-function base station to the communication user, h nlos It follows a complex Gaussian distribution with mean 0 and variance 1.

[0016] Compared with the prior art, the advantages of the present invention are:

[0017] 1) In the method of the present invention, the dual-function base station needs to communicate with the communication user and the radar user by multicast and unicast mixed signals, and multiplex the transmitted multicast and unicast mixed signals to perform the perception task. Under the condition that the communication performance requirements of the communication user and the radar user in the communication perception integrated system and the perception performance requirements of the radar user and the radar target are met, the physical layer security of the mixed multicast and unicast communication in the communication perception integrated system is studied. Compared with the previous communication perception integrated system which only perceives the radar target, the method of the present invention considers the radar user, and the dual-function base station both communicates with it and performs the perception task, that is, the object of communication and perception is the same, which truly realizes the integration of communication perception. In this scenario, the physical layer security of the communication perception integrated system is studied, and it is proposed to use multicast signals instead of artificial noise that does not carry any information to prevent unicast signals from being eavesdropped by radar targets as potential eavesdroppers. Compared with the use of artificial noise, it can not only save unnecessary power loss, but also protect the more private unicast signals from being eavesdropped by potential eavesdroppers. At the same time, the multicast signal can also transmit information securely with the user.

[0018] 2) The method of the present invention is suitable for complex ground scenarios. When establishing the power minimization optimization problem, it is taken into account that in practical applications, the channel state information of communication users is difficult to obtain perfectly. A bounded error is introduced into the modeling of the channel from the dual-function base station to the communication user, which can ensure the robustness of the integrated communication perception system.

[0019] 3) The method of the present invention considers the existence area of ​​the radar target as a continuous angle area rather than a fixed point, which can improve the robustness of the communication and perception integrated system. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flowchart of the overall implementation process of the method of the present invention;

[0021] Figure 2 A simple schematic diagram of the ISAC multicast and unicast communication model constructed by the method of the present invention;

[0022] Figure 3 The safety rate of the communication perception integrated system using the method of the present invention and the existing random error scheme, MUC method, and OMA method varies with the unicast signal communication rate threshold η u Comparison chart of the changing curves. DETAILED DESCRIPTION

[0023] The present invention is further described in detail below with reference to the accompanying drawings.

[0024] The present invention proposes a NOMA-assisted secure beamforming method with integrated multicast and unicast communication perception, and its overall implementation flow chart is as follows: Figure 1 As shown, it includes the following steps:

[0025] Step 1: Build an ISAC multicast and unicast communication model for the communication awareness integrated system, such as Figure 2 As shown in FIG. 1 , the model includes a dual-function base station (BS), two users, and a radar target. The dual-function base station is configured with a uniform linear array. The dual-function base station is used to perform communication and perception tasks. The two users are a communication user and a radar user. The communication user only needs to communicate with the dual-function base station. The radar user needs to communicate with the dual-function base station and be perceived by the dual-function base station. The communication intensity between the communication user and the dual-function base station is higher than the communication intensity between the radar user and the dual-function base station. The radar target will also act as a potential eavesdropper to eavesdrop on the private communication between the dual-function base station and the user.

[0026] Step 2: The dual-function base station simultaneously sends a multicast-unicast mixed signal to the communication user and the radar user. The radar target, which is a potential eavesdropper, eavesdrops on the unicast signal. At the same time, the dual-function base station uses the sent multicast-unicast mixed signal to sense the radar user and the radar target. The multicast-unicast mixed signal is reflected by the radar user and the radar target respectively, and the dual-function base station receives the radar echo signal. The multicast-unicast mixed signal x sent by the dual-function base station is expressed as x=w m s m +w u s u , the signal y received by the communication user c Expressed as The signal y received by the radar user r Expressed as The signal y that is intercepted by the radar target as a potential eavesdropper t Expressed as The radar echo signal y received by the dual-function base station BS Represented as y BS =ζ t αa(θ t ) H (θ t )x+ζ r βa(θ r ) H (θ r )x+n; wherein the power of the multicast signal in the multicast-unicast mixed signal is greater than the power of the unicast signal, w m s m represents the multicast signal in x, s m represents the symbol carrying multicast information, w m Indicates m The beamforming vector, w u s u represents a unicast signal in x, s u represents the unicast information bearing symbol, w u Indicates u The beamforming vector, s m and u All have unit power and are independent of each other, h c represents the channel from the dual-function base station to the communication user, () H is the conjugate transpose operation, n c represents the additive Gaussian white noise received by the communication user, n c The variance of represents the channel from the dual-function base station to the radar user, β represents the path loss from the dual-function base station to the radar user, and θ r represents the azimuth from the dual-function base station to the radar user, a(θ r) represents the radar user's steering vector, e is a natural constant, e = 2.71…, j is an imaginary unit, d represents the antenna spacing of the uniform linear array configured for the dual-function base station, λ represents the carrier wavelength, N represents the number of antennas of the uniform linear array configured for the dual-function base station, () T is the transpose operation, n r represents the additive white Gaussian noise received by the radar user, n r The variance of represents the channel from the dual-function base station to the radar target as a potential eavesdropper, α represents the path loss from the dual-function base station to the radar target as a potential eavesdropper, and θ t represents the azimuth from the dual-function base station to the radar target as a potential eavesdropper, a(θ t ) represents the guidance vector of the radar target as a potential eavesdropper, n t represents the additive white Gaussian noise received at the radar target as a potential eavesdropper, n t The variance of ζ t represents the reflection coefficient of the radar target, ζ r represents the reflection coefficient of the radar user, and n represents y BS The noise of n is σ 2 .

[0027] In this embodiment, h c Modeled as the Rice channel model, Where k is the Rice factor, k = 10, h los represents the line-of-sight link from the dual-function base station to the communication user, h nlos represents the non-line-of-sight link from the dual-function base station to the communication user, h nlos It obeys a complex Gaussian distribution with mean 0 and variance 1, that is,

[0028] Step 3: Under the premise that the communication user needs both multicast and unicast signals, and the power of the multicast signal is greater than the power of the unicast signal, the communication user uses NOMA to first decode the multicast signal, and uses NOMA's interference cancellation technology to eliminate the interference caused by the multicast signal to the unicast signal, and increases the SINR of the multicast signal received at the communication user. c,m Expressed as The SINR of the unicast signal received at the communication user c,u Expressed as Under the premise that the radar user only needs the multicast signal, the multicast signal receiving signal to noise ratio SINR at the radar user is calculated. r,m Expressed as Under the premise that the radar target as a potential eavesdropper does not know the decoding order of the communication user using NOMA decoding, the unicast signal receiving signal to noise ratio SINR at the radar target as a potential eavesdropper is calculated. t,u Expressed as The dual-function base station receives the radar echo signal y BS After that, in the BS Before decoding, y BS First multiply it by the corresponding weight vector, then the weight vector u of the radar target t and the radar user's steering vector a(θ r ) are orthogonal, the weight vector u of the radar user r and the guidance vector a(θ t ) are orthogonal, the output signal to interference and noise ratio SINR of the radar target at the dual-function base station is BS,t , The output signal to interference and noise ratio SINR of the radar user at the dual-function base station BS,r , Then the multicast signal communication rate R at the communication user c,m Expressed as The unicast signal communication rate R at the communication user c,u Expressed as The multicast signal communication rate R at the radar user r,m Expressed as The eavesdropping rate R of the unicast signal at the radar target as a potential eavesdropper t,u , Among them, || is the modulo operator, Tr() means finding the trace of the matrix, represents the covariance matrix of the multicast and unicast mixed signal x, A(θ t ) and A(θ r ) are introduced as intermediate quantities, A(θ t )=a(θ t ) H (θ t ), A(θ r )=a(θ r ) H (θ r ).

[0029] Step 4: Under the conditions of satisfying the multicast and unicast hybrid communication performance of communication users and radar users, the perception performance of radar users and radar targets, and suppressing the unicast eavesdropping performance of radar targets as potential eavesdroppers, a power minimization optimization problem is established, which is described as:

[0030]

[0031] Among them, min is the minimum function, st means "subject to...", p t is the objective function of the power minimization optimization problem, p t Indicates the transmit power of a dual-function base station, η u represents the unicast signal communication rate threshold, η m represents the multicast signal communication rate threshold, η t represents the unicast signal eavesdropping rate threshold, γ t represents the radar target output signal-to-interference-noise ratio threshold, γ r represents the radar user output signal-to-interference-noise ratio threshold, Θ t Indicates the existence area of ​​the radar target, which is a continuous angle area. represents the channel estimation value from the dual-function base station to the communication user, which is estimated by the existing technology, δ c represents the channel estimation error from the dual-function base station to the communication user, which is a bounded error, δ c Satisfy the condition ||δ c ||2≤∈ c ,||||2 is the binary norm operator,∈ c is the threshold, take ∈ c =0.1, constraint C1 ensures that the unicast signal communication rate at the communication user is greater than or equal to the set threshold, constraint C2 ensures that the multicast signal communication rate at the communication user is greater than or equal to the set threshold, constraint C3 ensures that the multicast signal communication rate at the radar user is greater than or equal to the set threshold, constraint C4 ensures that the unicast signal eavesdropping rate at the radar target as a potential eavesdropper is less than or equal to the set threshold, so as to achieve the purpose of suppressing eavesdropping, constraint C5 ensures that the output signal to interference and noise ratio of the radar target at the dual-function base station is greater than or equal to the set threshold, ensuring the perception performance, constraint C6 ensures that the output signal to interference and noise ratio of the radar user at the dual-function base station is greater than or equal to the set threshold, ensuring the perception performance, constraint C7 represents the imperfect channel state information constraint of the communication user, that is, there is a channel error in the channel from the dual-function base station to the communication user.

[0032] Step 5: The difficulty in solving the power minimization optimization problem established in step 4 is that θ t The uncertainty (θ t In a continuous angle region Θ t Inner) and δ c Therefore, for the power minimization optimization problem established in step 4, t Discretize and relax, and use the S-lemma to introduce δ c , rewrite constraint C1 into semi-positive definite matrix form Rewrite constraint C2 into semi-positive matrix form Then, we use the semi-definite relaxation technique (SDR) to convert Θ t The power minimization optimization problem after discretization relaxation and rewriting of constraints C1 and C2 is converted into a convex optimization problem; then the convex optimization problem is solved using a convex optimization solver such as CVX to obtain w u and w m Their respective solutions; among them, G u and G m is the intermediate quantity introduced, r u and r m is the intermediate quantity introduced, λ u and λ m is the non-negative auxiliary variable introduced, I N Represents the identity matrix of order N.

[0033] The feasibility and effectiveness of the method of the present invention are further illustrated by the following simulation.

[0034] In the simulation, the azimuth angle from the dual-function base station to the communication user is set to 0°, and the azimuth angle from the dual-function base station to the radar user is θ r Set to -30°, the azimuth angle θ from the dual-function base station to the radar target as a potential eavesdropper t The continuous angle area Θ t Set to 25° to 35°; n c Variance n r Variance n t Variance The variance of n, σ 2 Both are set to -30dbm; the path loss from the dual-function base station to the radar target as a potential eavesdropper is α = Ld t -2.4 , the path loss from the dual-function base station to the radar user β = Ld r -2.4 , L represents the path loss per unit distance (1m), L = 30dB, d t Indicates the distance between the dual-function base station and the radar target, d r represents the distance between the dual-function base station and the radar user, d t =d r =500m;ζ t =ζ r =1; Multicast signal communication rate threshold η m Set to 1 bit / s / Hz, the unicast signal eavesdropping rate threshold η t Set to 0.1 bit / s / Hz, radar target output signal-to-interference-noise ratio threshold γ tand radar user output signal-to-interference-noise ratio threshold γ r Both are set to 15db.

[0035] In the simulation, the methods used for comparison include random error scheme, MUC method, and OMA method. Among them, the random error scheme refers to the channel estimation error from the dual-function base station to the communication user that satisfies the bounded error ||δ c ||2≤∈ c The method is randomly generated under the condition of , and the azimuth from the dual-function base station to the radar target as a potential eavesdropper is randomly generated between 25° and 35°; the MUC (Multicast and Unicast Communications) method refers to not considering the system security, that is, not adding constraints to suppress unicast eavesdropping; the OMA method refers to a method formed by replacing the NOMA technology in the method of the present invention with the OMA (Orthogonal Multiple Access) technology.

[0036] Figure 3 The safety rate of the communication perception integrated system using the method of the present invention and the existing random error scheme, MUC method, and OMA method is given as the unicast signal communication rate threshold η u The curve comparison chart of the changes. Figure 3 It can be seen that as the unicast signal communication rate threshold η u The performance requirements of unicast signal communication are also improved. The method of the present invention takes into account the security of the integrated communication perception system and designs a robust security beam. Although it will cause some power loss, as shown in the figure, the method of the present invention can achieve a higher security rate, ensuring the secure communication of the integrated communication perception system, and is superior to other comparison methods. Other comparison methods cannot effectively suppress eavesdropping due to technical limitations or failure to consider system security performance. Therefore, as the unicast signal communication rate threshold η u With the improvement of the security rate, the eavesdropping rate of the comparison method is also improved to a certain extent, so the security rate of the comparison method will be lower than that of the method of the present invention.

Claims

1. A NOMA-assisted secure beamforming method with integrated multicast and unicast communication perception, characterized in that The following steps are involved: Step 1: For the integrated communication and perception system, an ISAC multicast and unicast communication model is constructed. The model includes a dual-function base station, two users, and a radar target. The dual-function base station is configured with a uniform linear array. The dual-function base station is used to perform communication and perception tasks. The two users are a communication user and a radar user. The communication user only needs to communicate with the dual-function base station. The radar user needs to communicate with the dual-function base station and be perceived by the dual-function base station. The communication intensity between the communication user and the dual-function base station is higher than the communication intensity between the radar user and the dual-function base station. The radar target will also act as a potential eavesdropper to eavesdrop on the private communication between the dual-function base station and the user. Step 2: The dual-function base station simultaneously sends a multicast-unicast mixed signal to the communication user and the radar user. The radar target, which is a potential eavesdropper, eavesdrops on the unicast signal. At the same time, the dual-function base station uses the sent multicast-unicast mixed signal to sense the radar user and the radar target. After the multicast-unicast mixed signal is reflected by the radar user and the radar target, the dual-function base station receives the radar echo signal. The multicast and unicast mixed signal x sent by the dual-function base station is expressed as x=w m s m +w u s u , the signal y received by the communication user c Expressed as The signal y received by the radar user r Expressed as The signal y that is intercepted by the radar target as a potential eavesdropper t Expressed as The radar echo signal y received by the dual-function base station BS Represented as y BS =ζ t αa(θ t ) H (θ t )x+ζ r βa(θ r ) H (θ r )x+n; Among them, the power of the multicast signal in the multicast-unicast mixed signal is greater than the power of the unicast signal, w m s m represents the multicast signal in x, s m represents the symbol carrying multicast information, w m Indicates m The beamforming vector, w u s u represents a unicast signal in x, s u represents the unicast information bearing symbol, w u Indicates u The beamforming vector, s m and u All have unit power and are independent of each other, h c represents the channel from the dual-function base station to the communication user, () H is the conjugate transpose operation, n c represents the additive Gaussian white noise received by the communication user, n c The variance of represents the channel from the dual-function base station to the radar user, β represents the path loss from the dual-function base station to the radar user, and θ r represents the azimuth from the dual-function base station to the radar user, a(θ r ) represents the radar user's steering vector, e is a natural constant, j is an imaginary unit, d is the antenna spacing of the uniform linear array configured for the dual-function base station, λ is the carrier wavelength, N is the number of antennas of the uniform linear array configured for the dual-function base station, () T is the transpose operation, n r represents the additive white Gaussian noise received by the radar user, n r The variance of represents the channel from the dual-function base station to the radar target as a potential eavesdropper, α represents the path loss from the dual-function base station to the radar target as a potential eavesdropper, and θ t represents the azimuth from the dual-function base station to the radar target as a potential eavesdropper, a(θ t ) represents the guidance vector of the radar target as a potential eavesdropper, n t represents the additive white Gaussian noise received at the radar target as a potential eavesdropper, n t The variance of ζ t represents the reflection coefficient of the radar target, ζ r represents the reflection coefficient of the radar user, and n represents y BS The noise of n is σ 2 ; Step 3: Under the premise that the communication user needs both multicast and unicast signals, and the power of the multicast signal is greater than the power of the unicast signal, the communication user uses NOMA to first decode the multicast signal, and uses NOMA's interference cancellation technology to eliminate the interference caused by the multicast signal to the unicast signal, and increases the SINR of the multicast signal received at the communication user. c,m Expressed as The SINR of the unicast signal received at the communication user c,u Expressed as Under the premise that the radar user only needs the multicast signal, the signal-to-interference-and-noise ratio (SINR) of the multicast signal received at the radar user is calculated. r,m Expressed as Under the premise that the radar target as a potential eavesdropper does not know the decoding order of the communication user using NOMA decoding, the unicast signal receiving signal to noise ratio SINR at the radar target as a potential eavesdropper is calculated. t,u Expressed as The weight vector u of the radar target t and the radar user's steering vector a(θ r ) are orthogonal, the weight vector u of the radar user r and the guidance vector a(θ t ) are orthogonal, the output signal to interference and noise ratio SINR of the radar target at the dual-function base station is BS,t , The output signal to interference and noise ratio SINR of the radar user at the dual-function base station BS,r , Then the multicast signal communication rate R at the communication user c,m Expressed as The unicast signal communication rate R at the communication user c,u Expressed as The multicast signal communication rate R at the radar user r,m Expressed as The eavesdropping rate R of the unicast signal at the radar target as a potential eavesdropper t,u , Among them, | | is the modulo operator, Tr( ) means finding the trace of the matrix, represents the covariance matrix of the multicast and unicast mixed signal x, A(θ t ) and A(θ r ) are introduced as intermediate quantities, A(θ t )=a(θ t ) H (θ t ), A(θ r )=a(θ r ) H (i r ); Step 4: Under the conditions of satisfying the multicast and unicast hybrid communication performance of communication users and radar users, the perception performance of radar users and radar targets, and suppressing the unicast eavesdropping performance of radar targets as potential eavesdroppers, a power minimization optimization problem is established, which is described as: Among them, p t is the objective function of the power minimization optimization problem, p t Indicates the transmit power of a dual-function base station, η u represents the unicast signal communication rate threshold, η m represents the multicast signal communication rate threshold, η t represents the unicast signal eavesdropping rate threshold, γ t represents the radar target output signal-to-interference-noise ratio threshold, γ r represents the radar user output signal-to-interference-noise ratio threshold, Θ t Indicates the existence area of ​​the radar target, which is a continuous angle area. represents the channel estimation value from the dual-function base station to the communication user, δ c represents the channel estimation error from the dual-function base station to the communication user, which is a bounded error, δ c Satisfy the condition ||δ c ||2≤∈ c , || ||2 is the binary norm operator, ∈ c is the threshold value; Step 5: For the power minimization optimization problem established in step 4, t Discretize and relax, and use the S-lemma to introduce δ c , rewrite constraint C1 into semi-positive definite matrix form Rewrite constraint C2 into semi-positive matrix form Then, using the semi-positive definite relaxation technique, Θ t The power minimization optimization problem after discretization relaxation and rewriting of constraints C1 and C2 is converted into a convex optimization problem; then the convex optimization problem is solved using a convex optimization solver to obtain w u and w m Their respective solutions; among them, G u and G m is the intermediate quantity introduced, r u and r m is the intermediate quantity introduced, λ u and λ m is the non-negative auxiliary variable introduced, I N Represents the identity matrix of order N.

2. The NOMA-assisted secure beamforming method with integrated multicast and unicast communication perception according to claim 1 is characterized in that In step 2, h c Modeled as the Rice channel model, Where k is the Rice factor, h los represents the line-of-sight link from the dual-function base station to the communication user, h nlos represents the non-line-of-sight link from the dual-function base station to the communication user, h nlos It follows a complex Gaussian distribution with mean 0 and variance 1.

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