A method and system for 6g covert communication assisted by an antenna movable jammer

Abstract

This invention discloses a 6G covert communication method and system assisted by a mobile jammer, relating to the field of sixth-generation mobile communication technology. The method includes: defining a cooperative jammer antenna position vector, thereby obtaining the main channel from the base station to the legitimate receiver, the leaked channel to the eavesdropper, and the field-effect channel matrix from the jammer to each node, which varies with position. The achievable communication rate of the legitimate receiver is derived, and a binary hypothesis testing model using KL divergence as a covert measure is established at the eavesdropper. With minimizing the KL divergence as the objective, the optimal solutions for the base station transmit covariance matrix, the jammer artificial noise covariance matrix, and the antenna position vector are obtained through alternating optimization iterations under multiple constraints. Finally, based on the optimal position solution, a stepper motor is driven to move the antenna, and the base station and the jammer configure precoding according to the obtained covariance matrix and transmit signals synchronously.

Description

Technical Field

[0001] This invention belongs to the field of sixth-generation mobile communication technology, and particularly relates to a 6G covert communication method and system assisted by an antenna-movable jammer. Background Technology

[0002] The sixth-generation mobile communication (6G) is evolving towards integrated air-space-ground communication, ubiquitous intelligent interconnection, and ultimate physical layer security. Covert communication, as a core security technology to ensure undetectable communication activities and defend against unauthorized reconnaissance, has become a key research focus in 6G security architecture. Movable antennas (MAs) can dynamically adjust their physical position to actively reshape the spatial channel phase distribution, releasing additional spatial degrees of freedom. Compared to traditional fixed-position multi-antenna systems, movable antenna technology can more effectively overcome spatial correlation limitations, providing a new path to improve the security and reliability of communication systems. In multiple-input multiple-output (MIMO) covert communication systems, introducing cooperative jammers to emit artificial noise to mask legitimate communication activities is an effective means of achieving highly covert and highly reliable transmission.

[0003] However, current covert communication solutions for 6G evolution have the following limitations: First, existing cooperative jammers generally employ fixed-position antenna architectures, making it impossible to flexibly reshape the jamming channel characteristics by dynamically changing the physical location of the antennas. In complex 6G scattering environments where legitimate receivers and eavesdroppers are at close range, fixed-position antennas struggle to accurately suppress the eavesdropper's signal detection capabilities, resulting in a rigid bottleneck in improving concealment performance.

[0004] Secondly, existing technologies generally assume, ideally, that legitimate receivers can completely eliminate artificial noise through successive interference cancellation (SIC). This assumption differs significantly from the engineering realities of 6G ubiquitous IoT, where lightweight terminals have limited computing power and radio frequency hardware suffers from nonlinear distortion. In real-world scenarios without ideal SIC, this will lead to severe deviations in the estimation of legitimate communication rates, making it difficult to guarantee transmission reliability.

[0005] Third, most existing solutions only optimize the signal transmission covariance matrix of the base station or jammer separately, without incorporating the physical location of the antenna into a unified joint optimization framework. This makes it impossible to achieve deep coordination between antenna spatial location control and transmission power allocation, and makes it difficult to fully tap the performance potential of movable antennas for covert communication.

[0006] Fourth, to meet the actual deployment requirements of 6G covert communication, the system must simultaneously meet multiple stringent constraints such as non-serial interference cancellation reception, physical antenna collision prevention, and node transmit power limitation. However, existing technologies lack a systematic joint optimization scheme that uses Kullback-Leibler divergence as a covertness metric under such strong physical constraints.

[0007] Therefore, a technical solution is urgently needed to solve the above technical problems. Summary of the Invention

[0008] To address the aforementioned technical problems, this invention proposes a 6G covert communication method assisted by a mobile antenna jammer, comprising: Define the antenna position vector of the cooperative jammer. Based on the antenna position vector, obtain the main communication channel matrix from the base station to the legitimate receiver and the information leakage channel matrix from the base station to the eavesdropper. Establish the field effect channel matrix from the cooperative jammer to each receiving node, which changes dynamically with the antenna position vector. Based on the field-effect channel matrix, the achievable communication rate of the legitimate receiver is derived, and a binary hypothesis testing model is established at the eavesdropper, using KL divergence as a measure of concealment. With the goal of minimizing the KL divergence, under multiple constraints, the optimal solutions for the base station's transmitted signal covariance matrix, the cooperative jammer's artificial noise covariance matrix, and the antenna position vector are iteratively solved using an alternating optimization method. The stepper motor is driven to move each transmitting antenna to the target physical coordinates according to the optimal solution of the antenna position vector. The base station and the cooperative jammer configure spatial precoding according to the transmitted signal covariance matrix and the artificial noise covariance matrix respectively and transmit signals synchronously.

[0009] Furthermore, defining the cooperative jammer antenna position vector also includes: establishing the convex feasible region of the antenna position vector based on the minimum physical isolation distance constraint between adjacent antennas and the sliding rail boundary constraint.

[0010] Furthermore, before deriving the achievable communication rate of the legitimate receiver, the following steps are included: deriving the achievable communication rate of the legitimate receiver under the condition that the artificial noise from the cooperative jammer causes co-channel interference to the legitimate receiver and cannot be eliminated by serial interference cancellation methods.

[0011] Furthermore, the multiple constraints include: the lower bound of the achievable communication rate, the upper bound of the transmit power, the maximum transmit power of the cooperative jammer, and the convex feasible region.

[0012] Furthermore, establishing the convex feasible region of the antenna position vector includes: in, For a convex feasible region, Let be the antenna position vector. The minimum physical isolation distance between adjacent antennas of the cooperative jammer. For the cooperative jammer The location of each transmitting antenna This represents the total number of transmitting antennas of the cooperative jammer. The total length of the one-dimensional linear slide rail of the cooperative interference machine.

[0013] Furthermore, establishing the field-effect channel matrix from the cooperative jammer to each receiving node, which dynamically changes with the antenna position vector, includes: in, The vector of antenna position Dynamically changing cooperative interference machine up to the first The field-effect channel matrix of each receiving node. , It is a legitimate receiver. As a listener, For the first The receiver array response matrix of each receiving node. For the first The number of receiving antennas per receiving node For cooperative jamming machines up to the first The number of signal propagation paths for each receiving node For the first The multipath complex fading diagonal matrix of each receiving node The vector of antenna position Dynamically changing launch steering matrix, This is the matrix conjugate transpose operation; calculate The Line 1 Column elements include: in, The air channel wavelength corresponding to the system's operating carrier frequency. For the first The absolute physical coordinates of the movable transmitting antenna. For the cooperative jammer to be sent to the first The first receiving node The departure angle of a multipath signal.

[0014] Furthermore, the binary hypothesis testing model includes: in, The vector of antenna position The dynamically changing receive covariance matrix when the base station is not transmitting a signal. The vector of antenna position The dynamically changing received covariance matrix when a base station transmits signals. The vector of antenna position The dynamically changing field-effect channel matrix from the cooperative jammer to the eavesdropper. For the covariance matrix of the artificial noise of the cooperative interference machine, The equivalent noise floor variance of the listener's receiver. It is the identity matrix. This is the information leakage channel matrix from the base station to the eavesdropper. The base station transmit signal covariance matrix; Using KL divergence as a measure of concealment includes: in, As a measure of concealment, The number of antennas for the eavesdropper. For matrix determinant operations, For matrix trace operations, for The inverse matrix.

[0015] Furthermore, the achievable communication rates of a legitimate receiver are derived as follows: in, The achievable communication rate for a legitimate receiver. The vector of antenna position The dynamically changing field-effect channel matrix from the cooperative jammer to the legitimate receiver. This is the main communication channel matrix from the base station to the legitimate receiver. The base station transmit signal covariance matrix, It is the identity matrix. For matrix determinant operations, For the covariance matrix of the artificial noise of the cooperative interference machine, For the equivalent noise floor variance of a legitimate receiver, This is the matrix conjugate transpose operation.

[0016] Furthermore, the optimal solutions for the base station's transmitted signal covariance matrix, the cooperative jammer's artificial noise covariance matrix, and the antenna position vector are obtained through iterative solutions using an alternating optimization method, including: In each round, the covariance matrix of the base station's transmitted signal is completed. Artificial noise covariance matrix of cooperative interference machine With antenna position vector After solving the problem sequentially, the convergence condition is checked to complete the iteration. The convergence condition check includes: when the decrease in KL divergence between two consecutive complete iterations is less than a preset convergence threshold. If the number of iterations reaches the preset maximum number of iterations, the iteration is terminated and the optimal decision set is output. , This is the optimal solution for the covariance matrix of the base station's transmitted signal. The optimal solution for the artificial noise covariance matrix of the cooperative jammer. This is the optimal solution for the antenna position vector.

[0017] This invention also proposes a 6G covert communication system assisted by an antenna-movable jammer, comprising: A field-effect channel matrix module is established to define the antenna position vector of the cooperative jammer. Based on the antenna position vector, the main communication channel matrix from the base station to the legitimate receiver and the information leakage channel matrix from the base station to the eavesdropper are obtained. A field-effect channel matrix from the cooperative jammer to each receiving node is established, which dynamically changes with the antenna position vector. The module for calculating the concealment metric is used to derive the achievable communication rate of the legitimate receiver based on the field-effect channel matrix, and to establish a binary hypothesis testing model at the eavesdropper, using KL divergence as the concealment metric. The optimal solution calculation module is used to iteratively solve the optimal solutions of the base station's transmitted signal covariance matrix, the cooperative jammer's artificial noise covariance matrix, and the antenna position vector under multiple constraints by using an alternating optimization method, with the goal of minimizing the KL divergence. The location scheduling and transmission signal module is used to drive a stepper motor to move each transmitting antenna to the target physical coordinates according to the optimal solution of the antenna position vector. The base station and the cooperative jammer configure spatial precoding according to the transmission signal covariance matrix and the artificial noise covariance matrix respectively and transmit signals synchronously.

[0018] like Figure 4 , Figure 5 and Figure 6 As shown, compared with the prior art, the present invention has the following advantages and technical effects: 1. By setting the transmitting antenna of the cooperative jammer on a one-dimensional linear slide rail and establishing a field-effect channel matrix that dynamically changes with the antenna position, the physical constraints of traditional fixed-position antennas are broken, enabling the system to actively change the phase distribution of the multipath environment and achieve precise control of the characteristics of the jamming channel and on-demand reshaping of spatial nulls.

[0019] 2. By abandoning the assumption of ideal serial interference elimination, the artificial noise generated by the cooperative jammer is directly modeled as co-channel interference of the legitimate receiver. This makes the system model fit the actual communication scenario with limited hardware computing power, avoids the distortion of legitimate communication rate prediction caused by the over-idealization of the theoretical model, and ensures the reliability of communication in the actual physical environment.

[0020] 3. By using a joint optimization problem with minimizing the Kullback-Leibler divergence as the stealth metric, the covariance matrix of the base station transmitted signal, the covariance matrix of the cooperative jammer's artificial noise, and the physical coordinates of the cooperative jammer's antenna are simultaneously incorporated into the solution system, achieving multi-dimensional collaborative scheduling in the spatial and energy domains and maximizing the stealth performance of the system.

[0021] 4. By introducing linear inequalities to construct a convex feasible region for antenna position movement, the physical constraints for collision avoidance are transformed into standard linear constraints, which reduces the complexity of solving position variables and ensures that the optimization results can be directly sent to the stepper motor and baseband hardware for execution, thus possessing high engineering feasibility. Attached Figure Description

[0022] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart of the method in Embodiment 1 of the present invention; Figure 2 This is a system structure diagram of Embodiment 2 of the present invention; Figure 3 This is a schematic diagram of the system architecture and multipath field effect model of Embodiment 2 of the present invention; Figure 4 This is a comparison chart of the concealment performance of the present invention and the traditional fixed antenna (FPA) jamming architecture under different target rate requirements; Figure 5 This is a comparison chart of the concealment performance of the present invention and the traditional fixed antenna (FPA) jamming architecture under different jamming transmit power budgets; Figure 6 This is a simulation trend diagram showing the change in the system concealment performance of the present invention with the length of the antenna normalized moving area (spatial degrees of freedom). Detailed Implementation

[0023] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0024] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0025] Example 1 like Figure 1 As shown, this embodiment proposes a 6G covert communication method assisted by an antenna-movable jammer, applied to a multi-input multi-output communication system including a base station, a legitimate receiver, a listener, and a cooperative jammer. The transmitting antenna of the cooperative jammer is mounted on a one-dimensional linear slide rail. The method specifically includes the following steps: Step 101: Define the antenna position vector of the cooperative jammer. Based on the antenna position vector, obtain the main communication channel matrix from the base station to the legitimate receiver and the information leakage channel matrix from the base station to the eavesdropper. Establish the field effect channel matrix from the cooperative jammer to each receiving node, which changes dynamically with the antenna position vector. Specifically, defining the cooperative jammer antenna position vector also includes: establishing the convex feasible region of the antenna position vector based on the minimum physical isolation distance constraint between adjacent antennas and the sliding rail boundary constraint.

[0026] Preferably, the base station is equipped with A fixed transmitting antenna, equipped with a legitimate receiver. A fixed receiving antenna, equipped by the eavesdropper The jammer is equipped with a fixed receiving antenna and features A uniform linear array of transmitting antennas, with an array aperture of [missing information]. Define the antenna position vector of the cooperative jammer as follows: , As a matrix transpose, the antenna position must satisfy the convex feasible region.

[0027] This embodiment sets system parameters based on a typical 6G MIMO covert communication simulation scenario and engineering hardware constraints. For example, the system transmission bandwidth is 10 MHz, and the receiver's equivalent noise floor variance is calibrated to... Base station configuration The transmitting antenna, the legitimate receiver, and the eavesdropper are each configured separately. , Root receiving antenna, cooperative jammer configuration The one-dimensional sliding rail movable transmitting antenna has a large-scale path loss index set to 3.0.

[0028] Specifically, establishing the convex feasible region of the antenna position vector includes: in, For a convex feasible region, Let be the antenna position vector. The minimum physical isolation distance between adjacent antennas of the cooperative jammer (to prevent coupling effects between adjacent movable antennas). For the cooperative jammer The location of each transmitting antenna This represents the total number of transmitting antennas of the cooperative jammer. The total length of the one-dimensional linear slide rail of the cooperative interference machine.

[0029] For example, let the total length of the one-dimensional linear guide rail of the cooperative interference machine be... ,in The air channel wavelength corresponding to the system's operating carrier frequency is set as follows: To avoid physical collisions between antennas, the minimum physical isolation distance between adjacent antennas of the cooperative jammer is set to [value missing]. .

[0030] The convex feasible region is then established as follows: The main communication channel matrix from the base station to the legitimate receiver is obtained using an independent Rayleigh fading model. And the information leakage channel matrix from the base station to the eavesdropper .

[0031] Configure the interference channel to include Multipath, among which, Representing the legitimate receiver and the eavesdropper respectively, generate the first... Receiver array response matrix of each receiving node With the Multipath complex fading diagonal matrix of receiving nodes Specifically, establishing the field-effect channel matrix from the cooperative jammer to each receiving node, which dynamically changes with the antenna position vector, includes: in, The vector of antenna position Dynamically changing cooperative interference machine up to the first The field-effect channel matrix of each receiving node. , It is a legitimate receiver. As a listener, For the first The receiver array response matrix of each receiving node. For the first The number of receiving antennas per receiving node For cooperative jamming machines up to the first The number of multipaths per receiving node For the first The multipath complex fading diagonal matrix of each receiving node The vector of antenna position Dynamically changing launch steering matrix, This is the matrix conjugate transpose operation; calculate The Line 1 Column elements include: in, The air channel wavelength corresponding to the system's operating carrier frequency. For the first The absolute physical coordinates of the movable transmitting antenna. For the cooperative jammer to be sent to the first The first receiving node The departure angle (AoD) of a multipath signal.

[0032] Preferably, in order to achieve Dynamic reconstruction involves the cooperative jammer communicating with each receiving node via orthogonal pilot signals, utilizing conventional channel estimation algorithms such as least squares or least mean square error. Complex fading coefficient, angle of arrival, and departure angle Furthermore, based on the complex fading coefficient, a system is constructed. ;according to Combined with the fixed element spacing and the estimated angle of arrival, the array steering vector is generated using the formula for a standard uniform linear array or a uniform planar array. In combination with the above The cooperative jammer will acquire , With conjugate transpose Cascaded multiplication is used to obtain the field effect matrix under the current antenna position topology in real time. .

[0033] Step 102: Based on the field-effect channel matrix, derive the achievable communication rate of the legitimate receiver, and establish a binary hypothesis testing model at the eavesdropper, using KL divergence (Kullback-Leibler divergence) as a measure of concealment. Specifically, before deriving the achievable communication rate of the legitimate receiver, the following steps are also included: deriving the achievable communication rate of the legitimate receiver under the condition that the artificial noise from the cooperative jammer causes co-channel interference to the legitimate receiver and cannot be eliminated by serial interference cancellation methods.

[0034] Specifically, the achievable communication rates of a legitimate receiver are derived as follows: in, The achievable communication rate for a legitimate receiver. The vector of antenna position The dynamically changing field-effect channel matrix from the cooperative jammer to the legitimate receiver. This is the main communication channel matrix from the base station to the legitimate receiver. The base station transmit signal covariance matrix, It is the identity matrix. For matrix determinant operations, For the covariance matrix of the artificial noise of the cooperative interference machine, For the equivalent noise floor variance of a legitimate receiver, This is the matrix conjugate transpose operation.

[0035] Specifically, the binary hypothesis testing model includes: in, The vector of antenna position The dynamically changing receive covariance matrix when the base station is not transmitting a signal. The vector of antenna position The dynamically changing received covariance matrix when a base station transmits signals. The vector of antenna position The dynamically changing field-effect channel matrix from the cooperative jammer to the eavesdropper. For the covariance matrix of the artificial noise of the cooperative interference machine, The equivalent noise floor variance of the listener's receiver. It is the identity matrix. This is the information leakage channel matrix from the base station to the eavesdropper. The base station transmit signal covariance matrix; Using KL divergence as a measure of concealment includes: in, As a measure of concealment, The number of antennas for the eavesdropper. For matrix determinant operations, For matrix trace operations, for The inverse matrix.

[0036] Step 103: With the goal of minimizing the KL divergence, under multiple constraints, the optimal solutions for the base station's transmitted signal covariance matrix, the cooperative jammer's artificial noise covariance matrix, and the antenna position vector are iteratively solved using an alternating optimization method. Specifically, the multiple constraints include: the lower bound of the achievable communication rate, the upper bound of the transmit power, the maximum transmit power of the cooperative jammer, and the convex feasible region.

[0037] Preferably, the minimum achievable communication rate of a legitimate receiver. (The lower bound of the achievable communication rate, for example) ), maximum transmission power of base stations (Upper limit of transmit power, for example) ), Maximum transmit power of the cooperative jammer (For example and the convex feasible region of the antenna's physical location. Assuming constraints, construct a global joint optimization problem: Specifically, the optimal solutions for the base station's transmitted signal covariance matrix, the cooperative jammer's artificial noise covariance matrix, and the antenna position vector obtained through iterative optimization using an alternating optimization method include: In each round, the covariance matrix of the base station's transmitted signal is completed. Artificial noise covariance matrix of cooperative interference machine With antenna position vector After solving the problem sequentially, the convergence condition is checked to complete the iteration. The convergence condition check includes: when the decrease in KL divergence between two consecutive complete iterations is less than a preset convergence threshold. If the number of iterations reaches the preset maximum number of iterations, the iteration is terminated and the optimal decision set is output. , This is the optimal solution for the covariance matrix of the base station's transmitted signal. The optimal solution for the artificial noise covariance matrix of the cooperative jammer. This is the optimal solution for the antenna position vector.

[0038] Preferably, an alternating optimization algorithm is used, such as the Flat Block Coordinate Descent (FCD) method, which decouples the non-convex problem by alternately fixing some variables and then solves the problem sequentially using numerical computing tools such as the MOSEK solver. , and antenna position vector The subproblems are solved until the algorithm converges.

[0039] Preferred, fixed and Call the MOSEK solver to... The subproblems with variables are solved directly as semidefinite programming (SDP) problems.

[0040] Preferred, fixed and For non-convex rate constraints in scenarios without SiC Principal component matrices are extracted through eigenvalue decomposition and transformed into convex approximation constraints of a first-order Taylor expansion using the continuous convex approximation (SCA), thereby obtaining the optimal solution. .

[0041] Preferred, fixed and Calculate the objective function For vectors The partial derivative gradient is used, and the maximum gradient norm threshold is limited to 10.0. The antenna coordinates are updated using the backtracking line search technique, and the results are projected back into the convex feasible region. .

[0042] Preferably, until the KL divergence decreases below the convergence threshold. Alternatively, it can reach a maximum of 250 iterations to output the optimal decision set. .

[0043] Preferably, for the above-mentioned high-dimensional non-convex multivariate joint optimization problem, the alternating direction multiplier method (ADMM), heuristic search algorithms (such as particle swarm optimization algorithm PSO, genetic algorithm GA) or intelligent optimization algorithms based on deep reinforcement learning (DRL) can also be used.

[0044] Step 104: Drive the stepper motor to move each transmitting antenna to the target physical coordinates according to the optimal solution of the antenna position vector. The base station and the cooperative jammer configure spatial precoding according to the transmitted signal covariance matrix and the artificial noise covariance matrix respectively and transmit signals synchronously.

[0045] Preferably, the system controller will calculate the optimal solution of the antenna position vector. The data is sent to the cooperating jammer, which drives its internal stepper motor and transmission device to precisely move each transmitting antenna to the physical coordinates corresponding to the one-dimensional slide rail. At this position, the base station and the cooperating jammer, respectively, [follow certain commands / methods]. and The spatial precoding allocation of the signal is performed, and confidential communication signals and artificial noise signals are transmitted simultaneously.

[0046] Preferably, (1) the system main control unit extracts the calculated optimal antenna position vector. This signal is converted into a pulse control signal, which drives a stepper motor on a one-dimensional slide rail to translate the four cooperative interference transmitting antennas to the absolute coordinates. At this point, phase reshaping of the space interference channel is completed.

[0047] (2) Base station and cooperative jammer according to It assigns corresponding beamforming weights and transmit power to its multiple radio frequency transmission links.

[0048] (3) The base station transmits confidential data streams, while the cooperating jammer injects artificial noise synchronously. In this state, the rate of the legitimate receiving link is strictly guaranteed to be within the threshold boundary of 0.5 bps / Hz, and the excess spatial degrees of freedom are fully suppressed into the background noise of the eavesdropper, achieving highly covert communication that approaches the physical limit.

[0049] Example 2 like Figure 2 and 3 As shown, this embodiment proposes a 6G covert communication system assisted by an antenna-movable jammer, which specifically includes the following modules: A field-effect channel matrix module is established to define the antenna position vector of the cooperative jammer. Based on the antenna position vector, the main communication channel matrix from the base station to the legitimate receiver and the information leakage channel matrix from the base station to the eavesdropper are obtained. A field-effect channel matrix from the cooperative jammer to each receiving node is established, which dynamically changes with the antenna position vector. The module for calculating the concealment metric is used to derive the achievable communication rate of the legitimate receiver based on the field-effect channel matrix, and to establish a binary hypothesis testing model at the eavesdropper, using KL divergence as the concealment metric. The optimal solution calculation module is used to iteratively solve the optimal solutions of the base station's transmitted signal covariance matrix, the cooperative jammer's artificial noise covariance matrix, and the antenna position vector under multiple constraints by using an alternating optimization method, with the goal of minimizing the KL divergence. The location scheduling and transmission signal module is used to drive a stepper motor to move each transmitting antenna to the target physical coordinates according to the optimal solution of the antenna position vector. The base station and the cooperative jammer configure spatial precoding according to the transmission signal covariance matrix and the artificial noise covariance matrix respectively and transmit signals synchronously.

[0050] Since the system technical solution of this embodiment 2 is based on the technical solution of embodiment 1, it will not be described again.

Claims

1. A 6G covert communication method assisted by a mobile antenna jammer, characterized in that, include: Define the antenna position vector of the cooperative jammer. Based on the antenna position vector, obtain the main communication channel matrix from the base station to the legitimate receiver and the information leakage channel matrix from the base station to the eavesdropper. Establish the field effect channel matrix from the cooperative jammer to each receiving node, which changes dynamically with the antenna position vector. Based on the field-effect channel matrix, the achievable communication rate of the legitimate receiver is derived, and a binary hypothesis testing model is established at the eavesdropper, using KL divergence as a measure of concealment. With the goal of minimizing the KL divergence, under multiple constraints, the optimal solutions for the base station's transmitted signal covariance matrix, the cooperative jammer's artificial noise covariance matrix, and the antenna position vector are iteratively solved using an alternating optimization method. The stepper motor is driven to move each transmitting antenna to the target physical coordinates according to the optimal solution of the antenna position vector. The base station and the cooperative jammer configure spatial precoding according to the transmitted signal covariance matrix and the artificial noise covariance matrix respectively and transmit signals synchronously.

2. The 6G covert communication method assisted by a mobile antenna jammer as described in claim 1, characterized in that, Defining the cooperative jammer antenna position vector also includes: establishing the convex feasible region of the antenna position vector based on the minimum physical isolation distance constraint between adjacent antennas and the sliding rail boundary constraint.

3. The 6G covert communication method assisted by a movable antenna jammer as described in claim 1, characterized in that, Before deriving the achievable communication rate of the legitimate receiver, the following steps are also taken: under the condition that the artificial noise of the cooperative jammer causes co-channel interference to the legitimate receiver and cannot be eliminated by serial interference cancellation methods, the achievable communication rate of the legitimate receiver is derived.

4. The 6G covert communication method assisted by a mobile antenna jammer as described in claim 2, characterized in that, The multiple constraints include: the lower bound of the achievable communication rate, the upper bound of the transmit power, the maximum transmit power of the cooperative jammer, and the convex feasible region.

5. The 6G covert communication method assisted by a mobile antenna jammer as described in claim 2, characterized in that, Establishing the convex feasible region of the antenna position vector includes: in, For a convex feasible region, Let be the antenna position vector. The minimum physical isolation distance between adjacent antennas of the cooperative jammer. For the cooperative jammer The location of each transmitting antenna This represents the total number of transmitting antennas of the cooperative jammer. The total length of the one-dimensional linear slide rail of the cooperative interference machine.

6. The 6G covert communication method assisted by a mobile antenna jammer as described in claim 1, characterized in that, Establishing the field-effect channel matrix from the cooperative jammer to each receiving node, which dynamically changes with the antenna position vector, includes: in, The vector of antenna position Dynamically changing cooperative interference machine up to the first The field-effect channel matrix of each receiving node. , It is a legitimate receiver. As a listener, For the first The receiver array response matrix of each receiving node. For the first The number of receiving antennas per receiving node For cooperative jamming machines up to the first The number of multipaths per receiving node For the first The multipath complex fading diagonal matrix of each receiving node The vector of antenna position Dynamically changing launch steering matrix, This is the matrix conjugate transpose operation; calculate The Line number Column elements include: in, The air channel wavelength corresponding to the system's operating carrier frequency. For the first The absolute physical coordinates of the movable transmitting antenna. For the cooperative jammer to be sent to the first The first receiving node The departure angle of a multipath signal.

7. The 6G covert communication method assisted by a mobile antenna jammer as described in claim 6, characterized in that, The binary hypothesis testing model includes: in, The vector of antenna position The dynamically changing receive covariance matrix when the base station is not transmitting a signal. The vector of antenna position The dynamically changing received covariance matrix when a base station transmits signals. The vector of antenna position The dynamically changing field-effect channel matrix from the cooperative jammer to the eavesdropper. For the covariance matrix of the artificial noise of the cooperative interference machine, The equivalent noise floor variance of the listener's receiver. It is the identity matrix. This is the information leakage channel matrix from the base station to the eavesdropper. The base station transmit signal covariance matrix; Using KL divergence as a measure of concealment includes: in, As a measure of concealment, The number of antennas for the eavesdropper. For matrix determinant operations, For matrix trace operations, for The inverse matrix.

8. The 6G covert communication method assisted by a mobile antenna jammer as described in claim 3, characterized in that, The achievable communication rates of a legitimate receiver include: in, The achievable communication rate for a legitimate receiver. The vector of antenna position The dynamically changing field-effect channel matrix from the cooperative jammer to the legitimate receiver. This is the main communication channel matrix from the base station to the legitimate receiver. The base station transmit signal covariance matrix, It is the identity matrix. For matrix determinant operations, For the covariance matrix of the artificial noise of the cooperative interference machine, For the equivalent noise floor variance of a legitimate receiver, This is the matrix conjugate transpose operation.

9. The 6G covert communication method assisted by a movable antenna jammer as described in claim 1, characterized in that, The optimal solutions obtained iteratively using the alternating optimization method for the base station's transmitted signal covariance matrix, the cooperative jammer's artificial noise covariance matrix, and the antenna position vector include: In each round, the covariance matrix of the base station's transmitted signal is completed. Artificial noise covariance matrix of cooperative interference machine With antenna position vector After solving the problem sequentially, the convergence condition is checked to complete the iteration. The convergence condition check includes: when the decrease in KL divergence between two consecutive complete iterations is less than a preset convergence threshold. If the number of iterations reaches the preset maximum number of iterations, the iteration is terminated and the optimal decision set is output. , This is the optimal solution for the covariance matrix of the base station's transmitted signal. The optimal solution for the artificial noise covariance matrix of the cooperative jammer. This is the optimal solution for the antenna position vector.

10. A 6G covert communication system assisted by a mobile antenna jammer, characterized in that, include: A field-effect channel matrix module is established to define the antenna position vector of the cooperative jammer. Based on the antenna position vector, the main communication channel matrix from the base station to the legitimate receiver and the information leakage channel matrix from the base station to the eavesdropper are obtained. A field-effect channel matrix from the cooperative jammer to each receiving node is established, which dynamically changes with the antenna position vector. The module for calculating the concealment metric is used to derive the achievable communication rate of the legitimate receiver based on the field-effect channel matrix, and to establish a binary hypothesis testing model at the eavesdropper, using KL divergence as the concealment metric. The optimal solution calculation module is used to iteratively solve the optimal solutions of the base station's transmitted signal covariance matrix, the cooperative jammer's artificial noise covariance matrix, and the antenna position vector under multiple constraints by using an alternating optimization method, with the goal of minimizing the KL divergence. The location scheduling and transmission signal module is used to drive a stepper motor to move each transmitting antenna to the target physical coordinates according to the optimal solution of the antenna position vector. The base station and the cooperative jammer configure spatial precoding according to the transmission signal covariance matrix and the artificial noise covariance matrix respectively and transmit signals synchronously.

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