Covert communication method and device

Abstract

The invention provides a covert communication method and device which can be used in the technical field of communication, and the method comprises the steps: receiving a communication beam forming parameter and a communication beam forming parameter which are obtained by solving an optimization problem; predicting current state information based on the historical state information of the eavesdropper in the previous time slot; transmitting a superposed signal containing a sensing signal and current state information based on the sensorship beam forming parameter, so that a jammer interferes with an eavesdropper; the intelligent reflecting surface based on communication beam forming parameters and optimal phase shift optimization communicates with a hidden user side; when a sensing echo signal is received, accurate state information of an eavesdropper is estimated and used as historical state information. In the scheme, related parameters obtained by solving an optimization problem are received to realize optimization of transmitted beam forming, then state information of an eavesdropper is tracked and sensed and is sent to a jammer to prevent eavesdropping of the eavesdropper, and a base station communicates with a hidden user side with the help of an intelligent reflecting surface with optimized phase shift, so that the hidden user side is protected from being stolen. Therefore, the purpose of improving the covert communication rate is achieved.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a covert communication method and device. Background Art

[0002] With the rapid development of wireless communication technology, people are increasingly relying on wireless networks for information transmission. However, a large amount of important sensitive information, such as identity information, confidential documents, etc., is transmitted in open wireless networks, increasing the risk of being eavesdropped. Therefore, information security issues are receiving more and more attention.

[0003] In order to protect the communication content from being detected by eavesdroppers, covert communication technology came into being. The purpose of covert communication is to achieve information transmission between the base station (such as Alice) and the covert user (such as Bob) without being detected by eavesdroppers (such as Willie). Covert communication technology achieves the concealment of communication by utilizing the randomness and uncertainty of the channel, as well as the superposition and cover of signals. In a covert communication system, a covert user refers to a user whose information transmission needs to be carried out without being detected by eavesdroppers. At the same time, a public user refers to a user whose information transmission does not need to be hidden, but is carried out normally.

[0004] In the existing covert communication system, a communication model that only uses an intelligent reflective surface to assist or the simplest three-node model is adopted. During the covert communication process, it is impossible to interfere with the eavesdropper, resulting in a low covert communication rate. Summary of the invention

[0005] In view of this, an embodiment of the present invention provides a covert communication method and device to achieve the purpose of improving the covert communication rate.

[0006] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0007] A first aspect of an embodiment of the present invention discloses a covert communication method, which is applied to a base station, wherein the base station is respectively connected to a jammer, an intelligent reflective surface, and a central controller for communication, and the method includes:

[0008] Receiving communication beamforming parameters and synaesthesia beamforming parameters obtained by solving an optimization problem by a central controller; the optimization problem is used to optimize the transmit beamforming of the base station and the phase shift of the smart reflective surface to maximize the concealed communication rate between the base station and the concealed user terminal;

[0009] For each time slot in the eavesdropper's service cycle, if the time slot is the first time slot, the known initial state information of the eavesdropper is used as the current state information; if the time slot is not the first time slot, the current state information is predicted based on the historical state information of the eavesdropper obtained in the previous time slot;

[0010] Transmitting a first superposition signal including a perception signal and the current state information based on the synaesthesia beamforming parameter, so that the jammer sends a jamming signal to the eavesdropper after receiving the current state information;

[0011] Based on the communication beamforming parameters, a first message signal to be sent to the hidden user terminal is sent to the smart reflecting surface, so that the smart reflecting surface sends the first message signal to the hidden user terminal based on an optimal phase shift; the optimal phase shift is obtained by the central controller by solving the optimization problem and sent to the smart reflecting surface;

[0012] When a perception echo signal generated by the eavesdropper reflecting the perception signal is received, accurate state information of the eavesdropper is estimated based on the perception echo signal, and the accurate state information is used as historical state information for the next time slot.

[0013] Preferably, when receiving the perception echo signal generated by the eavesdropper reflecting the perception signal, estimating and obtaining accurate status information of the eavesdropper based on the perception echo signal includes:

[0014] When receiving a perception echo signal generated by the eavesdropper reflecting the perception signal, extracting relevant information of the eavesdropper from the perception echo signal;

[0015] The accurate status information of the eavesdropper is obtained by utilizing the relevant information and a tracking model constructed based on the extended Kalman filter technology.

[0016] Preferably, the method further comprises:

[0017] If the sensing echo signal is not received, the current state information is used as the historical state information of the next time slot.

[0018] Preferably, the method further comprises:

[0019] If there is a first message signal to be sent to the hidden user end and a second message signal to be sent to the public user end, based on the communication beamforming parameters, a second superimposed signal including the first message signal and the second message signal is sent to the smart reflecting surface, so that the smart reflecting surface sends the second superimposed signal to the hidden user end and the public user end based on the optimal phase shift.

[0020] A second aspect of an embodiment of the present invention discloses a covert communication method, which is applied to a central controller, wherein the central controller is respectively connected to a base station and an intelligent reflective surface for communication, and the method includes:

[0021] According to the multiple constraints obtained in advance, a non-convex optimization problem is constructed; the constraints include: communication concealment constraint, perception concealment constraint, total power constraint, perception capability constraint, radar detection constraint and public user communication quality constraint; the optimization problem is used to optimize the transmit beamforming of the base station and the phase shift of the smart reflection surface to maximize the concealed communication rate between the base station and the concealed user terminal;

[0022] Decoupling the optimization problem into multiple sub-problems;

[0023] Using an alternating iterative optimization algorithm to solve each of the sub-problems, and obtain communication beamforming parameters, synaesthesia beamforming parameters and an optimal phase shift;

[0024] The communication beamforming parameters and the synaesthesia beamforming parameters are sent to the base station, and the optimal phase shift is sent to the smart reflective surface.

[0025] A third aspect of an embodiment of the present invention discloses a covert communication device, which is applied to a base station. The base station is respectively connected to a jammer, an intelligent reflective surface, and a central controller for communication. The device includes:

[0026] A receiving unit, used to receive the communication beamforming parameters and the synaesthesia beamforming parameters obtained by solving the optimization problem by the central controller; the optimization problem is used to optimize the transmit beamforming of the base station and the phase shift of the smart reflective surface to maximize the concealed communication rate between the base station and the concealed user terminal;

[0027] A prediction unit is used for predicting the current state information based on the known initial state information of the eavesdropper for each time slot in the eavesdropper's service period if the time slot is the first time slot, and predicting the current state information based on the historical state information of the eavesdropper obtained in the previous time slot if the time slot is not the first time slot;

[0028] A first sending unit, configured to transmit a first superposition signal including a perception signal and the current state information based on the synaesthesia beamforming parameter, so that the jammer sends a jamming signal to the eavesdropper after receiving the current state information;

[0029] A second sending unit is used to send a first message signal to be sent to the hidden user terminal to the smart reflecting surface based on the communication beamforming parameter, so that the smart reflecting surface sends the first message signal to the hidden user terminal based on an optimal phase shift; the optimal phase shift is obtained by the central controller by solving the optimization problem and sent to the smart reflecting surface;

[0030] The sensing unit is configured to estimate accurate state information of the eavesdropper based on the sensing echo signal when receiving the sensing echo signal generated by the eavesdropper reflecting the sensing signal, and use the accurate state information as historical state information of the next time slot.

[0031] Preferably, the sensing unit is specifically used for:

[0032] When receiving a perception echo signal generated by the eavesdropper reflecting the perception signal, extracting relevant information of the eavesdropper from the perception echo signal;

[0033] The accurate status information of the eavesdropper is obtained by utilizing the relevant information and a tracking model constructed based on the extended Kalman filter technology.

[0034] Preferably, the sensing unit is further used for:

[0035] If the sensing echo signal is not received, the current state information is used as the historical state information of the next time slot.

[0036] Preferably, the second sending unit is further used for:

[0037] If there is a first message signal to be sent to the hidden user end and a second message signal to be sent to the public user end, based on the communication beamforming parameters, a second superimposed signal including the first message signal and the second message signal is sent to the smart reflecting surface, so that the smart reflecting surface sends the second superimposed signal to the hidden user end and the public user end based on the optimal phase shift.

[0038] A fourth aspect of an embodiment of the present invention discloses a concealed communication device, which is applied to a central controller, wherein the central controller is respectively connected to a base station and an intelligent reflective surface for communication, and the device comprises:

[0039] A construction unit is used to construct a non-convex optimization problem according to multiple constraints obtained by pre-analysis; the constraints include: communication concealment constraint, perception concealment constraint, total power constraint, perception capability constraint, radar detection constraint and public user communication quality constraint; the optimization problem is used to optimize the transmit beamforming of the base station and the phase shift of the smart reflection surface to maximize the concealed communication rate between the base station and the concealed user terminal;

[0040] A solving unit, used for decoupling the optimization problem to obtain a plurality of sub-problems; solving each of the sub-problems using an alternating iterative optimization algorithm to obtain communication beamforming parameters, synaesthesia beamforming parameters and an optimal phase shift;

[0041] The third sending unit is used to send the communication beamforming parameter and the synaesthesia beamforming parameter to the base station, and send the optimal phase shift to the smart reflection surface.

[0042] Based on a covert communication method and device provided by the above-mentioned embodiment of the present invention, a communication beamforming parameter and a synaesthesia beamforming parameter obtained by solving an optimization problem by a central controller are received; the optimization problem is used to optimize the transmit beamforming of the base station and the phase shift of the intelligent reflective surface to maximize the covert communication rate between the base station and the covert user terminal; for each time slot in the eavesdropper's service period, if the time slot is the first time slot, the known initial state information of the eavesdropper is used as the current state information; if the time slot is not the first time slot, the current state information is predicted based on the historical state information of the eavesdropper obtained in the previous time slot; based on the synaesthesia beamforming parameters, a transmission signal containing a perception signal and the current state information is transmitted; The first superposition signal of the state information enables the jammer to send a jamming signal to the eavesdropper after receiving the current state information; based on the communication beamforming parameters, the first message signal to be sent to the concealed user end is sent to the intelligent reflecting surface, so that the intelligent reflecting surface sends the first message signal to the concealed user end based on the optimal phase shift; the optimal phase shift is obtained by the central controller by solving the optimization problem and sent to the intelligent reflecting surface; when the perceived echo signal generated by the eavesdropper reflecting the perceived signal is received, the accurate state information of the eavesdropper is estimated based on the perceived echo signal, and the accurate state information is used as the historical state information of the next time slot. In this scheme, the relevant parameters obtained by solving the optimization problem are received to optimize the transmit beamforming, and then the state information of the perceived eavesdropper is tracked and sent to the jammer to prevent the eavesdropper from eavesdropping. With the help of the intelligent reflecting surface with optimized phase shift, the base station communicates with the concealed user end, thereby achieving the purpose of improving the concealed communication rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0044] Figure 1 An architectural diagram of a covert communication system disclosed in an embodiment of the present invention;

[0045] Figure 2 A time slot division diagram disclosed in an embodiment of the present invention;

[0046] Figure 3A flow chart of a covert communication method disclosed in an embodiment of the present invention;

[0047] Figure 4 A flowchart of another covert communication method disclosed in an embodiment of the present invention;

[0048] Figure 5 A schematic diagram of the convergence of the EKF method disclosed in an embodiment of the present invention;

[0049] Figure 6 A comparison diagram of the trajectory predicted by the EKF method disclosed in an embodiment of the present invention and the actual trajectory;

[0050] Figure 7 A curve diagram showing the relationship between the concealed transmission rate and the number of iterations disclosed in an embodiment of the present invention;

[0051] Figure 8 A curve diagram showing the relationship between the concealed transmission rate and the total power disclosed in the embodiment of the present invention;

[0052] Fig. 9 A curve diagram showing the relationship between the concealed transmission rate and the number of IRS units disclosed in an embodiment of the present invention;

[0053] Fig.10 A curve diagram showing the relationship between the concealed transmission rate and the concealed tolerance value disclosed in an embodiment of the present invention;

[0054] Fig.11 A structural diagram of a covert communication device disclosed in an embodiment of the present invention;

[0055] Fig.12 This is a structural diagram of another covert communication device disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] In this application, the terms "comprises", "comprising" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element.

[0058] As can be seen from the background technology, in the existing covert communication system, a communication model that only uses an intelligent reflective surface to assist or the simplest three-node model is adopted. During the covert communication process, it is impossible to interfere with the eavesdropper, resulting in a low covert communication rate.

[0059] Therefore, an embodiment of the present invention discloses a covert communication method and device. In this scheme, relevant parameters obtained by solving the optimization problem are received to optimize the transmit beamforming, and then the state information of the eavesdropper is tracked and sensed and sent to the jammer to prevent the eavesdropper from eavesdropping. With the help of the intelligent reflection surface with optimized phase shift, the base station communicates with the covert user terminal, thereby achieving the purpose of improving the covert communication rate.

[0060] like Figure 1 As shown, it is an architecture diagram of a covert communication system disclosed in an embodiment of the present invention. The covert communication system includes: a base station Alice, an intelligent reflection surface IRS, a jammer Jammer, a central controller, a covert user terminal Bob and a public user terminal Grace.

[0061] In the covert communication system, the base station optimized by transmit beamforming first predicts the state information of the eavesdropper Willie and sends it to the jammer to counter the eavesdropper. Then, with the assistance of the jammer, the base station uses the smart reflective surface optimized by the optimal phase shift to communicate with the covert user end and the public user end.

[0062] Specifically, the central controller constructs a non-convex optimization problem according to multiple constraints obtained in advance; decouples the optimization problem to obtain multiple sub-problems; uses an alternating iterative optimization algorithm to solve each sub-problem to obtain communication beamforming parameters, synaesthesia beamforming parameters and an optimal phase shift; sends the communication beamforming parameters and synaesthesia beamforming parameters to a base station, and sends the optimal phase shift to the smart reflector.

[0063] The constraints include: communication concealment constraint, perception concealment constraint, total power constraint, perception capability constraint, radar detection constraint and public user communication quality constraint; the optimization problem is used to optimize the base station's transmit beamforming and the phase shift of the smart reflection surface to maximize the covert communication rate between the base station and the hidden user end.

[0064] The base station receives the communication beamforming parameters and the synaesthesia beamforming parameters obtained by the central controller through solving the optimization problem.

[0065] For each time slot in the eavesdropper's service cycle, if the time slot is the first time slot, the base station uses the known initial state information of the eavesdropper as the current state information; if the time slot is not the first time slot, the current state information is predicted based on the historical state information of the eavesdropper obtained in the previous time slot.

[0066] The base station optimizes the transmit beamforming using the communication beamforming parameters and the synaesthesia beamforming parameters, and transmits the superposition signal of the current state information and the perception signal based on the synaesthesia beamforming parameters, so that the jammer sends a jamming signal to the eavesdropper.

[0067] With the assistance of the jammer, the base station sends a superimposed signal (including messages to be sent to the hidden user end and messages to be sent to the public user end) to the smart reflective surface based on the communication beamforming parameters.

[0068] The smart reflective surface receives the best phase shift and optimizes it, so that when receiving the superimposed signal sent by the base station, it forwards it to the hidden user end and the public user end based on the best phase shift.

[0069] When the base station receives the sensing echo signal generated by the eavesdropper's reflected sensing signal, it estimates the accurate state information of the eavesdropper based on the sensing echo signal and uses the accurate state information as the historical state information of the next time slot.

[0070] Among them, the eavesdropper can be a drone with eavesdropping capabilities; the hidden user terminal, the public user terminal and the jammer are all equipped with a single antenna.

[0071] The base station is equipped with an M uniform linear array antenna. In order to facilitate the separation deployment, all antennas of the base station are divided into two groups, namely M 1 and M 2 , M 1 +M 2 =M.M 1 For the synaesthesia stage, M 2 Used in the simple communication stage.

[0072] The smart reflector is composed of N uniform array antennas. The phase shift matrix of the smart reflector can be expressed as: ,in , diag symbol represents a diagonal matrix, j is the imaginary number symbol, and e is the natural logarithm.

[0073] The location coordinates of the base station are , the hidden user terminal location coordinates are , the jammer's position coordinates are , the position coordinates of the smart reflective surface are .

[0074] like Figure 2 As shown, a time slot division diagram disclosed in an embodiment of the present invention is shown.

[0075] The eavesdropper's service time T is divided into I time slots, and the time of each time slot is T / I. The position coordinates of the eavesdropper in time slot i are , whose speed is .

[0076] Then the state of the eavesdropper in time slot i can be expressed as .

[0077] It should be noted that, in order to consider a more realistic situation, the channel state information of the eavesdropper is not available and needs to be estimated and predicted by the base station. However, the channel state information of all legitimate users is available.

[0078] The drone eavesdropper maneuvers at high altitudes and attempts to monitor the communication between the base station and the hidden user. Assume that the eavesdropper's movement is a constant speed model. In order to ensure the security of communication, the base station uses the posterior state Predicting prior states .

[0079] like Figure 2 As shown, each time slot is divided into 4 stages, which are:

[0080] Prior state estimation phase: In this phase, the system predicts the current state information based on previous information.

[0081] ISAC (Integrated Sensing and Communication) phase: In this phase, the system performs communication and perception tasks simultaneously.

[0082] Communication Only stage: In this stage, the system only performs communication tasks and does not perform perception.

[0083] Posterior state estimation phase: In this phase, the system updates the current state information based on the information received by perception.

[0084] Specifically, for each time slot, in the a priori state estimation stage, the base station predicts the current state information (i.e., the a priori state of the current time slot) of the eavesdropper based on the state information of the eavesdropper estimated in the previous time slot (i.e., the a posteriori state of the previous time slot).

[0085] In the ISAC stage, the current state information and the perception signal are superimposed and transmitted based on the synaesthesia beamforming parameters.

[0086] It should be noted that in the present application, the initial state information of the eavesdropper is known. In the first time slot, the base station will transmit the initial state information as the current state information superimposed with the perception signal.

[0087] It can be understood that the current state information received by the jammer includes at least the location information of the eavesdropper, thereby sending a jamming signal to the eavesdropper.

[0088] In the pure communication stage, with the assistance of the jammer, the base station uses communication beamforming parameters and intelligent reflection surfaces to communicate with the public user end and to communicate covertly with the hidden user end.

[0089] In the a posteriori state estimation stage, a new measurement can be performed based on the perceived echo signal reflected by the eavesdropper to obtain accurate state information of the eavesdropper, which is the a posteriori state of the current time slot.

[0090] The analysis of the channel model, communication model and perception model related to the above process is as follows:

[0091] 1. Channel model:

[0092] Assume that all ground-to-air channels can be expressed as:

[0093] (1)

[0094] Where ρ is the reference power gain per meter, d ij represents the distance from user i to j, aw represents Alice and Willie, rw represents IRS and Willie, Jw represents Jammer and Willie, is the ground-to-space path loss index, g ij represents the connection vector between user i and user j.

[0095] In the above-mentioned embodiment of the present invention, the base station hopes to detect the presence of an eavesdropper while maintaining communication with the concealed communication terminal. ij is the channel gain (i.e., channel model) between user i and user j, with the first letter of the user's English abbreviation as the subscript. The English abbreviations of each participating user in the covert communication system have been given above. For example, the channel model of the base station-eavesdropper can be expressed as:

[0096] (2)

[0097] Among them, α aw is the perceived target reflectivity, θ aw Represents the angle between the base station and the eavesdropper. The vector It can be expressed as:

[0098] (3)

[0099] Where λ is the wavelength, d aw is the distance between two adjacent radar antennas. Generally, d aw=λ / 2.

[0100] 2. Communication model:

[0101] ISAC stage: In time slot i, in order to simultaneously sense and track the eavesdropper and communicate with the jammer, the base station transmits a superposition signal x containing the current state information and the sensed signal 1 , which can be expressed as:

[0102] (4)

[0103] in, and They are respectively represented as the communication beamforming vector and the sensing beamforming vector of the base station, and They are the signals for communicating with the jammer and for sensing eavesdroppers. The communication rate between the base station and the jammer can be expressed as:

[0104] (5)

[0105] Among them, h aJ represents the channel gain from the jammer to the base station; Represents the noise power or interference power generated by the jammer.

[0106] Pure communication stage: In time slot i, the jammer receives the current state information of the eavesdropper and transmits it with power P J Send interference signals to it to prevent eavesdroppers from monitoring. The base station will superimpose the signal x 2 Sent to two users, x 2 is a non-orthogonal multiple access (NOMA) signal, which can be expressed as:

[0107] (6)

[0108] in, Express satisfaction The NOMA communication symbol, and They are the information signals of the hidden user end and the public user end respectively. is the NOMA communication beamforming matrix, and They are and The beamforming vector of NOMA user The received signal can be expressed as:

[0109] (7)

[0110] in is the Gaussian white noise at node k, h ak represents the channel gain from user k to the base station, h rk represents the channel gain from IRS to user k, h ar represents the channel gain from the base station to the IRS, h Jr represents the channel gain from the jammer to the IRS, h ar represents the channel gain from the base station to the IRS, P J Represents power. Assuming that the hidden user end and the public user end are near users and far users respectively, in order to ensure the successive interference cancellation (SIC), the base station allocates more transmission power to send Rather than ,Right now .

[0111] In this application, it is assumed that there is perfect SIC at the hidden user end and the public user end, and the interference between the two users in receiving each other's signals does not need to be considered.

[0112] According to the NOMA principle, hidden user end detection And by using SIC to remove the corresponding interference, and then detect its own signal . Public users can use Correlated signals are detected by treating them as noise . Concealed user-side detection signal and The rate can be expressed as: and , where the signal-to-noise ratio can be expressed as: and , in addition, the communication rate at the public user end can be expressed as:

[0113] (8)

[0114] Among them, h ab represents the channel gain from the hidden user terminal to the base station, h rb represents the channel gain from IRS to the hidden user end, h Jr represents the channel gain from IRS to jammer, h Jb represents the channel gain from the hidden user end to the jammer, h ar represents the channel gain from the base station to the IRS, represents the channel gain from the public user end to the jammer, Indicates the channel gain from the public user end to the base station, represents the channel gain from the public user end to the IRS, P JIndicates power, Represents the interference power at the hidden user end.

[0115] It should be noted that in order for SIC to be feasible on a NOMA receiver, the achievable rate at which the public user detects its own messages should not exceed the achievable rate at which the covert user detects them. (That is, the radar detection constraint of the optimization problem). At the same time, in order to ensure the communication quality of the public user side, (i.e., the public user communication quality constraints of the optimization problem).

[0116] 3. Perception model:

[0117] It should be noted that this application aims to use the sensing signal of the base station to track the eavesdropper and send its current state information to the jammer, which then implements noise interference on it, thereby improving the system's concealment. In order to achieve effective interference, the base station needs to estimate the current accurate state information of the eavesdropper, thereby constructing a channel related to the eavesdropper.

[0118] It should be noted that the eavesdropper is generally an aerial target, usually moving at high speed. In order to improve the performance of covert transmission, this application adopts a tracking model based on the extended Kalman filter (EKF) to track and predict the position of the enemy target based on the estimated speed information. The details of the target tracking based on EKF are as follows:

[0119] This application only considers the direct link with the eavesdropper. Then the echo signal received by the base station can be expressed as:

[0120]

[0121] in is the noise signal at the base station, then the signal-to-noise ratio of the perceived echo signal received by the base station can be expressed as:

[0122] (9)

[0123] In addition, once the base station receives the sensing echo signal, it can obtain relevant information about the eavesdropper from it. aw and sensing echo signals The mutual information between the two is used as an indicator of radar target detection performance, because the mutual information can characterize the ability of the base station to How much information can be learned from Given.

[0124] In each time slot, the base station first predicts the current state information based on the state information of the eavesdropper estimated in the previous time slot, and sends the current state information to the jammer. With the help of the jammer's interference, the waveform of the NOMA signal (containing the messages to be sent to the hidden user end and the public user end) is designed. Subsequently, new measurements can be made based on the sensed echo signal, so that the new state of the eavesdropper can be estimated or predicted.

[0125] Specifically, consider that the speed of the eavesdropper in two consecutive time slots is almost the same, that is, the constant speed motion model. The state evolution prediction equation of the eavesdropper can be expressed as:

[0126] (10)

[0127] in, is the state transfer matrix. 3 and 0 3 are the 3×3 identity matrix and the zero matrix respectively. is the state evolution noise, is the state evolution covariance matrix. Therefore, the current accurate state information of the eavesdropper in time slot i can be expressed as , the prediction covariance matrix can be expressed as:

[0128] (11)

[0129] in, yes The covariance matrix of .

[0130] The measurement parameters are assumed to be , the parameter measurement model can be expressed as:

[0131] (12)

[0132] in, is the measurement function, is the measurement Gaussian noise. By linearizing the measurement model around the prediction model, the measurement model is transformed into:

[0133] (13)

[0134] in, express about The Jacobian matrix of . The accurate state information prediction equation (tracking model) of the eavesdropper in time slot i can be expressed as:

[0135] (14)

[0136] in, is the Kalman gain matrix, which is given by:

[0137] (15)

[0138] in, The parameter is The state evolution covariance matrix at .

[0139] Based on the covert communication system disclosed in the above embodiment of the present invention, Figure 3 FIG. 1 is a flow chart of a covert communication method disclosed in an embodiment of the present invention, which is applied to a base station. The method includes the following steps:

[0140] Step S101: receiving communication beamforming parameters and synaesthesia beamforming parameters obtained by solving an optimization problem by a central controller.

[0141] The optimization problem is used to optimize the base station's transmit beamforming and the phase shift of the smart reflective surface to maximize the covert communication rate between the base station and the covert user end.

[0142] For details on how the central controller solves the optimization problem, see Figure 4 Corresponding embodiments of the present invention.

[0143] Step S102: For each time slot in the eavesdropper's service cycle, if the time slot is the first time slot, the known initial state information of the eavesdropper is used as the current state information; if the time slot is not the first time slot, the current state information is predicted based on the historical state information of the eavesdropper obtained in the previous time slot.

[0144] The eavesdropper may be a drone, and the eavesdropper service period is the time period during which the drone is operating in the air and conducting eavesdropping.

[0145] Specifically, for each time slot, in the a priori state estimation stage, the base station predicts the current state information (i.e., the a priori state of the current time slot) of the eavesdropper based on the state information of the eavesdropper estimated in the previous time slot (i.e., the a posteriori state of the previous time slot).

[0146] It should be noted that the initial state information of the eavesdropper is known (can be obtained in advance through other methods). In the first time slot, the base station will transmit the initial state information as the current state information and superimpose it with the perception signal.

[0147] Step S103: transmitting a first superposition signal including the perception signal and the current state information based on the synaesthesia beamforming parameters, so that the jammer sends a jamming signal to the eavesdropper after receiving the current state information.

[0148] In step S103, the base station is equipped with an M uniform linear array antenna. In order to facilitate the separation deployment, all antennas of the base station are divided into two groups, namely, M 1 and M 2 , M 1 +M 2 =M.M 1 For the synaesthesia stage, M 2 Used in the simple communication stage.

[0149] In the specific implementation process of step S103, using M 1 A first superposition signal including the perception signal and current state information is transmitted based on the synaesthesia beamforming parameters.

[0150] Among them, the process of superposition of perception signals and current state information has been introduced in the analysis of the above communication model.

[0151] It can be understood that the current state information includes the location information of the eavesdropper, that is, the coordinate information. Therefore, the jammer receives the current state information and can send a jamming signal according to the location of the eavesdropper.

[0152] Step S104: Based on the communication beamforming parameters, the first message signal to be sent to the hidden user terminal is sent to the smart reflecting surface, so that the smart reflecting surface sends the first message signal to the hidden user terminal based on the optimal phase shift.

[0153] The optimal phase shift is obtained by solving the optimization problem by the central controller and sent to the smart reflective surface.

[0154] Smart reflective surface is a wireless communication technology that deploys a plane composed of a large number of low-cost passive reflective units in the communication environment to intelligently adjust the phase, amplitude and polarization of the reflected signal, thereby reconstructing the wireless propagation environment and significantly improving the performance of the wireless communication network.

[0155] In the embodiment of the present invention, the intelligent reflective surface serves as a relay between the base station and two users (Bob and Grace), thereby solving the problem that the base station and the two users cannot communicate due to the lack of a direct path due to geographical barriers.

[0156] In one embodiment, if there is a first message signal to be sent to a hidden user end and a second message signal to be sent to a public user end, a second superimposed signal including the first message signal and the second message signal is sent to the smart reflecting surface based on the communication beamforming parameters, so that the smart reflecting surface sends the second superimposed signal to the hidden user end and the public user end based on the optimal phase shift.

[0157] Specifically, using the M of the two antennas of the base station 2and communication beamforming parameters, and sending a second superposition signal including the first message signal and the second message signal to the smart reflective surface. The specific superposition process has been introduced in the above communication model.

[0158] Step S105: when a perception echo signal generated by the eavesdropper's reflected perception signal is received, accurate state information of the eavesdropper is estimated based on the perception echo signal, and the accurate state information is used as historical state information for the next time slot.

[0159] In the specific implementation process of step S105, when the perception echo signal generated by the eavesdropper's reflected perception signal is received, relevant information of the eavesdropper is extracted from the perception echo signal, and the relevant information includes: location information, speed information, etc. of the eavesdropper.

[0160] Then, the accurate status information of the eavesdropper is obtained by using the relevant information and the tracking model constructed based on the extended Kalman filter technology. For a specific explanation, please refer to the perception model part introduced in the above embodiment of the present invention.

[0161] Based on the covert communication method disclosed in the above embodiment of the present invention, in this scheme, the relevant parameters obtained by solving the optimization problem are received to optimize the transmit beamforming, and then the state information of the perceived eavesdropper is tracked and sent to the jammer to prevent the eavesdropper from eavesdropping. With the help of the intelligent reflective surface with optimized phase shift, the base station communicates with the hidden user terminal. The core innovation lies in the introduction of a dual concealment mechanism of communication and perception behavior, real-time perception capability to track and predict the trajectory of mobile eavesdroppers, and active defense is achieved through collaborative interference and IRS phase optimization, thereby achieving the purpose of increasing the covert communication rate.

[0162] like Figure 4 FIG. 1 is a flow chart of another covert communication method disclosed in an embodiment of the present invention. The method is applied to a central controller and includes the following steps:

[0163] Step S201: construct a non-convex optimization problem based on multiple constraints obtained through pre-analysis.

[0164] In step S201, the constraints include: communication concealment constraints, perception concealment constraints, total power constraints, perception capability constraints, radar detection constraints and public user communication quality constraints; the optimization problem is used to optimize the base station's transmit beamforming and the phase shift of the smart reflection surface to maximize the concealed communication rate between the base station and the concealed user terminal.

[0165] The analysis process of the radar detection constraint and the public user communication quality constraint has been introduced in the above embodiment of the present invention, and the analysis process of the communication concealment constraint and the perception concealment constraint is as follows:

[0166] First of all, it should be noted that the eavesdropper attempts to monitor whether the base station has any communication behavior and grasp its location. In actual scenarios, if either the perception signal or the communication signal is detected by the eavesdropper, there will be a risk of exposing the sending node. Therefore, unlike the prior art, the present application considers both the perception concealment constraint and the communication concealment constraint in one time slot.

[0167] 1. ISAC stage

[0168] In order to determine whether the signal is transmitted, the eavesdropper will perform a binary hypothesis test on the base station. Specifically, the null hypothesis indicates that the base station does not perform signal transmission or sensing tracking, and the alternative hypothesis It indicates that there is a base station for signal transmission or sensing tracking. Therefore, under this hypothesis test, the signal received by the eavesdropper can be expressed as:

[0169] (16)

[0170] in, is the Gaussian white noise at the eavesdropper.

[0171] When the null hypothesis When the alternative hypothesis is true, the received signal at the eavesdropper contains only additive noise. When it is established, the eavesdropper receives the signal from the base station. Their probability density function can be expressed as:

[0172] (17)

[0173] (18)

[0174] in, , .

[0175] This application uses the probability of false positives to measure the detection performance of eavesdroppers, which is defined as ,in is the false alarm probability, is the missed detection probability. D=0 means the eavesdropper’s detection judgment result is , D=1 means the judgment result is The best way to detect an eavesdropper is likelihood ratio detection, which is expressed as:

[0176] (19)

[0177] In order to limit the detection performance of the eavesdropper, the probability of misjudgment is limited to a certain range, which can be expressed as:

[0178] (20)

[0179] in, represents the hidden tolerance value, The smaller it is, the more concealed the system is.

[0180] The exact value of the likelihood ratio detection is difficult to calculate directly. By using the scaling method, the detection performance of the eavesdropper can be limited to a preset range. The probability of the eavesdropper's misjudgment is higher than its lower bound, which can be expressed as:

[0181] (twenty one)

[0182] in is the total variation distance. According to Pinsker's inequality, we know that:

[0183] (twenty two)

[0184] in represents KL divergence, and further we can get:

[0185] (twenty three)

[0186] Therefore, as long as If it is established, it can ensure that the detection performance of the eavesdropper is limited to the preset range. Next, the KL divergence at the eavesdropper in the ISAC stage is solved.

[0187] According to formula (17) and formula (18), the expression of KL divergence can be obtained as:

[0188] (twenty four)

[0189] Among them, n is the transmission packet length.

[0190] Theorem 1: Corresponding to , the average hidden constraint (i.e., perceptual hidden constraint) in the ISAC stage is expressed as:

[0191] (25)

[0192] in .

[0193] Proof: Known , we can get:

[0194] (26)

[0195] Considering the channel coefficient as a random variable, calculate the average concealment constraint:

[0196] (27)

[0197] As long as it satisfies ,So , Theorem 1 is proved.

[0198] 2. Simple communication stage

[0199] At this stage, the jammer is powered Send interference signals to the eavesdropper to prevent the eavesdropper from monitoring. The eavesdropper also performs binary hypothesis testing. Specifically, the null hypothesis indicates that the base station does not transmit signals to the hidden user end, and the alternative hypothesis is It means that there is a base station transmitting signals with the hidden user end. Therefore, under this hypothesis test, the signal received by the eavesdropper can be expressed as:

[0200] (28)

[0201] in is the jammer's interference power, is the Gaussian white noise at the eavesdropper, h Jw is the channel gain from the eavesdropper to the jammer, h Jr is the channel gain from IRS to jammer, h rw is the channel gain from the eavesdropper to the IRS.

[0202] When the null hypothesis When the condition holds, the received signal at the eavesdropper contains only additive noise and the jammer's interference signal. When it is established, the eavesdropper receives the signal from the base station. Their probability density function can be expressed as:

[0203] (29)

[0204] (30)

[0205] in:

[0206]

[0207]

[0208] Similarly, the probability of false positives is also used to measure the detection performance of the eavesdropper in the pure communication stage, which is defined as ,in is the false alarm probability, is the missed detection probability. D=1 means the eavesdropper’s detection judgment result is , D=0 means the judgment result is The best way to detect an eavesdropper is likelihood ratio detection, which is expressed as:

[0209] (31)

[0210] According to Theorem 1, the average concealment constraint in the pure communication phase can be obtained as , that is, the communication concealment constraint.

[0211] in .

[0212] In the above embodiment of the present invention, the communication rate R between the base station and the jammer has been introduced. c , obviously R c Need to be greater than or equal to the perception rate R s To ensure system performance, there is a perception capability constraint: R c ≥R s .

[0213] The total power constraint and the sensing capability constraint are obtained according to a preset threshold.

[0214] Specifically, the constructed non-convex optimization problem is as follows:

[0215] (32)

[0216] Among them, R b is the covert communication rate, P is the total power threshold, and Γ is the minimum perception threshold.

[0217] Step S202: decoupling the optimization problem into multiple sub-problems, and solving each sub-problem using an alternating iterative optimization algorithm to obtain communication beamforming parameters, synaesthesia beamforming parameters and an optimal phase shift.

[0218] In step S202, due to the high coupling of variables, the optimization problem is difficult to solve directly. Therefore, the problem is decoupled into three sub-problems. Subsequently, the alternating iterative optimization algorithm is introduced to solve these sub-problems in turn. Due to the non-convexity of the problem, it is impossible to find the optimal solution. However, the alternating iterative optimization algorithm, as a heuristic algorithm, can effectively solve the proposed problem.

[0219] The specific solution process is as follows:

[0220] 1) Optimizing phase shift: To simplify the problem, let:

[0221] (33)

[0222] Among them, Q is , a 1 to a 5 Used to equivalently replace the previous diag() and the content after it.

[0223] at the same time, , , , , , Then, the optimization problem can be transformed into:

[0224] (34)

[0225] First, by simplifying, we can get:

[0226] (35)

[0227] Then, introduce the auxiliary matrix:

[0228] (36)

[0229] Then, substituting formula (36) into (35) we can obtain:

[0230] (37)

[0231] According to the properties of the matrix trace, we can get To simplify further, let ,but ,in , .

[0232] Therefore, the optimization problem (34) is equivalent to:

[0233] (38)

[0234] Due to the existence of non-convex objective function and rank-one constraint, problem (38) is still a non-convex optimization problem. Then, the rank-one constraint is first relaxed using semidefinite relaxation (SDR).

[0235] Therefore, the optimization problem (38) can be rewritten as:

[0236] (39)

[0237] For this fractional programming problem, the Dinkelbach algorithm is used to solve the fractional programming problem. , .

[0238] Then, (38) can be reformulated as:

[0239] (40)

[0240] Where t is an auxiliary variable, and its iterative update formula is:

[0241] (41)

[0242] Where k is the number of iterations. Since t does not decrease after each iteration, t is updated alternately according to (41) to solve F in problem (40).

[0243] In general, F in problem (40) is not a rank-one matrix, that is , indicating that the optimal value of problem (40) only serves the upper bound of problem (38). Therefore, based on the solution of problem (40), the Gaussian randomization method is used to construct an approximate solution to problem (38).

[0244] Specifically, first decompose F, that is, ,in and are unitary matrices and diagonal matrices respectively. Then, we can get the suboptimal solution ,in It is a satisfying Any vector of .

[0245] In an independently generated Gaussian random vector In the example above, the best g is selected as the optimal solution. Finally, Can be Conclude.

[0246] Practice has shown that by using this method and performing sufficient randomization on r, the optimal objective value of problem (40) can be guaranteed to be approximately the optimal solution.

[0247] Finally, an algorithm for solving (34) is designed.

[0248] 2) Optimize beamforming w 2 : In the given and w 1 Under this condition, the optimization problem is still non-convex. So we first transform the optimization problem into a semi-positive programming problem and solve it using an iterative optimization algorithm based on the penalty function method. To further simplify, let:

[0249] (42)

[0250] but According to the properties of the matrix trace, we can get Similarly, we can get and . Then the optimization problem can be further transformed into:

[0251] (43)

[0252] For the penalty function method, the rank-one constraint is first transformed into an equality constraint, namely:

[0253] (44)

[0254] in and Represent the core norm and spectral norm of the matrix respectively. Then, the transformed constraints are incorporated into the objective function as penalty terms to solve problem (43) and obtain the following optimization problem:

[0255] (45)

[0256] in, represents the penalty parameter, which is used to punish the behavior that violates (44). According to the known If the value is small enough, the efficiency of solving problem (45) will decrease. Therefore, a two-level penalty-based algorithm will be used to solve problem (45).

[0257] In the inner layer, note that problem (45) is still non-convex. Therefore, applying The first-order Taylor expansion at The lower bound of ,in is the nth iteration of the Successive Convex Approximation (SCA) method with the given The eigenvector associated with the largest eigenvalue. Therefore, the optimization problem can be further rewritten as:

[0258] (46)

[0259] Problem (46) is a convex problem and can be solved efficiently using the existing CVX (Convex Optimization Toolbox) solver. In the outer layer, the penalty factor Will be gradually updated to a sufficiently small value as follows:

[0260] (47)

[0261] in, Represents a constant scaling factor.

[0262] 3) Optimize beamforming w 1 : The optimization problem can be expressed as:

[0263] (48)

[0264] This problem can be solved directly using the CVX toolkit.

[0265] Step S203: sending the communication beamforming parameters and the synaesthesia beamforming parameters to the base station, and sending the optimal phase shift to the smart reflective surface.

[0266] Based on a covert communication method disclosed in the above embodiment of the present invention, the non-convex joint optimization problem is decomposed into three sub-problems of perception beamforming, communication beamforming and IRS phase shift, and solved by an iterative optimization algorithm, wherein the optimal phase shift of the intelligent reflection surface is solved by semidefinite relaxation method and Gaussian randomization, the communication beamforming is solved by penalty function method and Dinkelbach algorithm, and the synaesthesia beamforming is solved by cvx solver. In this scheme, an iterative optimization algorithm is proposed to optimize the transmission beamforming of the intelligent reflection surface and the base station respectively by jointly optimizing the phase shift matrix of the intelligent reflection surface, synaesthesia beamforming and communication beamforming, thereby achieving a higher covert transmission rate than the traditional scheme.

[0267] The embodiment of the present invention also discloses a simulation method for a covert communication system, thereby verifying the effectiveness of the covert communication system and method disclosed in the above embodiment of the present invention, and at the same time respectively derives the effects of communication beamforming parameters, synaesthesia beamforming parameters and optimal phase shift on the covert communication performance.

[0268] like Figure 5 , which is a schematic diagram of the convergence of the EKF method disclosed in an embodiment of the present invention.

[0269] Figure 1 The accuracy of the EKF method in predicting the eavesdropper's trajectory was verified. To ensure the irregularity of the eavesdropper's trajectory in real scenarios, the embodiment of the present invention assumes that the heading angles of each time slot in the motion model are randomly generated, thereby generating a more random trajectory. By comparing the actual trajectory with the predicted trajectory, the EKF method reduces the mean square error from 100 to 10 in 30 iterations with the help of real-time sensory feedback. This dynamic tracking capability ensures that the system can actively adjust the beamforming and IRS configuration, overcoming the limitations of the static eavesdropping assumption in existing research.

[0270] like Figure 6 , which is a comparison diagram of the predicted trajectory and the actual trajectory of the EKF method disclosed in an embodiment of the present invention.

[0271] Among them, the actual trajectory of the aerial eavesdropper and the predicted trajectory using the EKF method are shown. Figure 6 The intersections in the figure represent the locations of the components of the covert communication system on the ground. Along the X-axis, they are: base station, jammer, intelligent reflective surface, covert user end, and public user end.

[0272] In the embodiment of the present invention, three benchmark schemes are also set, namely random IRS ISAC, IRS pure communication scheme and random IRS pure communication scheme, so as to focus on analyzing the synergy advantages between ISAC technology, intelligent IRS optimization and NOMA-enabled resource allocation strategy in a dynamic environment. The three benchmark schemes are detailed as follows:

[0273] Random IRS ISAC scheme: This scheme adopts the traditional ISAC system and randomly configures the IRS phase shift, retaining the dual functions of perception and communication but not optimizing the IRS reflection coefficient, that is, only optimizing the perception beamforming and communication beamforming of the base station. By comparing this scheme with the baseline scheme, we can explore the performance gains of dynamic IRS phase optimization and perception-communication joint resource allocation in improving concealment and spectrum efficiency.

[0274] IRS pure communication solution: This solution optimizes the IRS phase shift for communication tasks and decouples the perception function from the ISAC framework, that is, only the phase shift of the intelligent reflector and the communication beamforming of the base station are optimized. The goal of this solution is to quantify the security and throughput improvement achieved by the collaborative integration of perception and communication in the covert communication system and method disclosed in the above-mentioned embodiment of the present invention, especially for the dynamic environment where mobile eavesdroppers exist.

[0275] Random IRS pure communication scheme: This scheme combines random IRS phase shift with pure communication operation, which can separate the contributions of IRS optimization and ISAC dual functions, that is, only optimize the communication beamforming of the base station. This scheme highlights the limitations of static resource allocation and non-cooperative sensing-communication design, thus proving the necessity of the joint beamforming and trajectory-aware IRS configuration proposed in this paper.

[0276] like Figure 7 , which is a curve diagram showing the relationship between the concealed transmission rate and the number of iterations disclosed in an embodiment of the present invention.

[0277] Figure 7 The convergence characteristics of the covert transmission rate are demonstrated. The covert transmission rate quickly increases from 0.6bps / Hz to 5.1bps / Hz within 10 iterations and then tends to be stable.

[0278] It can be seen that the covert communication system and method disclosed in the above embodiment of the present invention not only have a faster convergence speed, but also have significantly better performance than random IRS ISAC, IRS pure communication and random IRS pure communication schemes. Combining the alternating optimization framework of semidefinite relaxation, penalty function method and Dinkelbach algorithm, fast convergence is achieved by decoupling non-convex subproblems, which reflects the efficiency of the decomposition technology in the covert communication system and method disclosed in the above embodiment of the present invention, ensuring that the scheme has practical application value in scenarios with limited resources and eavesdropping.

[0279] like Figure 8 , which is a curve diagram showing the relationship between the concealed transmission rate and the total power disclosed in an embodiment of the present invention.

[0280] Figure 8 The impact of total power budget on covert transmission rate under different schemes is demonstrated. Figure 8 The concealed transmission rate increases with the increase of the total power budget. This phenomenon is consistent with theoretical expectations, because increasing the total power budget can expand the feasible domain of beamforming optimization, thereby improving the flexibility of the solution.

[0281] It is worth noting that the covert communication system and method proposed in the above-mentioned embodiment of the present invention outperforms the other three benchmark schemes under any total power budget. This superiority stems from the joint optimization of perception-communication beamforming and IRS phase shift, which can dynamically control the interference at the eavesdropper and maximize resource utilization. Specifically, the random IRS pure communication scheme has a performance loss of 55.8% compared to the proposed scheme, highlighting the key role of IRS phase optimization and ISAC dual functions in power-constrained scenarios. In addition, the covert transmission rate of the IRS pure communication scheme without perception integration is 22.8% lower than that of the proposed scheme. This gap confirms the necessity of using ISAC dual-function signal synchronization to improve perception accuracy and communication security.

[0282] like Fig. 9 , which is a curve diagram showing the relationship between the concealed transmission rate and the number of IRS units disclosed in an embodiment of the present invention.

[0283] Fig. 9 The effect of the number of IRS units on the covert communication rate is demonstrated. When the number of IRS units increases from 15 to 45, the covert performance is significantly improved, confirming the key role of IRS in enhancing security and throughput. This improvement comes from the expansion of the degrees of freedom (DoF), which enables more accurate beamforming for covert users.

[0284] Although adding IRS units can improve the covert communication rate by providing additional DoF, practical constraints such as hardware cost, lightweight design and deployment portability need to be weighed. When the number of IRS units is 45, the performance of the covert communication system and method proposed in the above embodiment of the present invention is 53% and 14% better than the random IRS ISAC and random IRS pure communication schemes, respectively. This gap shows that it is necessary to fully unleash the potential of IRS by combining IRS phase optimization and perception-communication beamforming. In contrast, the IRS pure communication scheme without perception integration only achieves 4.4bps / Hz, highlighting the dual-function advantage of ISAC in balancing concealment and resource efficiency.

[0285] like Fig.10 , which is a curve diagram showing the relationship between the concealed transmission rate and the concealed tolerance value disclosed in an embodiment of the present invention.

[0286] Fig.10 The relationship between concealment tolerance and concealment transmission rate is shown. When the concealment tolerance is relaxed from 0.05 to 0.35, the concealment transmission rate of the concealment communication system and method proposed in the above embodiment of the present invention is increased from 2.4 bps / Hz to 4.9 bps / Hz. The other three benchmark schemes all show lower rates at each concealment tolerance.

[0287] This difference stems from the fact that the covert communication system and method proposed in the above-mentioned embodiment of the present invention can dynamically adjust the power allocation and IRS phase shift based on real-time perception feedback, and adaptively suppress Willie's detection capability while maximizing the legitimate channel gain.

[0288] Under strict concealment constraints, the slope of the curve is large; as the constraints are relaxed, the growth rate of each solution gradually slows down, mainly due to hardware limitations and interference elimination gain saturation. This phenomenon is easy to understand: when the concealment tolerance is low, the base station can allocate more power to the concealed signal, which promotes the increase of the concealed transmission rate; but as the constraints are further relaxed, the limited energy budget becomes the main factor restricting the growth of the concealment rate. This nonlinear characteristic highlights the necessity of joint trajectory prediction and resource optimization to maintain performance gains under dynamic security requirements.

[0289] Through the above simulation process, it can be known that the covert communication system and method disclosed in the above embodiment of the present invention innovatively introduces a dual concealment mechanism of communication and perception behavior to ensure security in resource-constrained environments. By decomposing the non-convex joint optimization problem into three sub-problems of perception beamforming, communication beamforming and IRS phase shift, an alternating optimization algorithm integrating semidefinite relaxation, penalty function method and Dinkelbach transform is developed to achieve a higher covert transmission rate than traditional schemes. Different from the existing research that relies on unrealistic static assumptions, the core innovation of the present invention lies in integrating real-time perception capabilities to track and predict the trajectory of mobile eavesdroppers, and realizing active defense through collaborative interference and IRS phase optimization. The simulation results verify the superiority of the covert communication system and method disclosed in the above embodiment of the present invention in terms of information security performance compared with the benchmark scheme.

[0290] like Fig.11 FIG. 1 is a structural diagram of a concealed communication device disclosed in an embodiment of the present invention. The device is applied to a base station and includes:

[0291] The receiving unit 111 is used to receive the communication beamforming parameters and the synaesthesia beamforming parameters obtained by the central controller by solving the optimization problem; the optimization problem is used to optimize the base station's transmit beamforming and the phase shift of the smart reflector to maximize the concealed communication rate between the base station and the concealed user terminal.

[0292] The prediction unit 112 is used for predicting the current state information of the eavesdropper based on the historical state information of the eavesdropper obtained in the previous time slot for each time slot in the eavesdropper's service cycle, if the time slot is the first time slot, using the known initial state information of the eavesdropper as the current state information, if the time slot is not the first time slot.

[0293] The first sending unit 113 is used to transmit a first superposition signal including a perception signal and current state information based on the synaesthesia beamforming parameter, so that the jammer sends a jamming signal to the eavesdropper after receiving the current state information.

[0294] The second sending unit 114 is used to send the first message signal to be sent to the hidden user end to the intelligent reflecting surface based on the communication beamforming parameters, so that the intelligent reflecting surface sends the first message signal to the hidden user end based on the optimal phase shift; the optimal phase shift is obtained by the central controller by solving the optimization problem and sent to the intelligent reflecting surface.

[0295] In one embodiment, the second sending unit 114 is specifically configured to:

[0296] If there is a first message signal to be sent to a hidden user end and a second message signal to be sent to a public user end, a second superimposed signal including the first message signal and the second message signal is sent to the smart reflecting surface based on the communication beamforming parameters, so that the smart reflecting surface sends the second superimposed signal to the hidden user end and the public user end based on the optimal phase shift.

[0297] The sensing unit 115 is configured to estimate accurate state information of the eavesdropper based on the sensing echo signal when receiving the sensing echo signal generated by the eavesdropper reflecting the sensing signal, and use the accurate state information as the historical state information of the next time slot.

[0298] In one embodiment, the sensing unit 115 is specifically configured to:

[0299] When the perception echo signal generated by the eavesdropper's reflected perception signal is received, relevant information of the eavesdropper is extracted from the perception echo signal; the accurate status information of the eavesdropper is obtained by using the relevant information and a tracking model constructed based on the extended Kalman filter technology.

[0300] In one embodiment, the sensing unit 115 is further configured to:

[0301] If the sensing echo signal is not received, the current state information is used as the historical state information of the next time slot.

[0302] Based on the above-mentioned covert communication device disclosed in the embodiment of the present invention, in this scheme, the relevant parameters obtained by solving the optimization problem are received to optimize the transmit beamforming, and then the state information of the perceived eavesdropper is tracked and sent to the jammer to prevent the eavesdropper from eavesdropping. With the help of the intelligent reflective surface with optimized phase shift, the base station communicates with the concealed user terminal. The core innovation lies in the introduction of a dual concealment mechanism of communication and perception behavior, real-time perception capability to track and predict the trajectory of mobile eavesdroppers, and active defense is achieved through collaborative interference and IRS phase optimization, thereby achieving the purpose of increasing the covert communication rate.

[0303] like Fig.12 FIG. 1 is a structural diagram of another covert communication device disclosed in an embodiment of the present invention, which is applied to a central controller and includes:

[0304] The construction unit 121 is used to construct a non-convex optimization problem according to multiple constraints obtained by pre-analysis.

[0305] Among them, the constraints include: communication concealment constraint, perception concealment constraint, total power constraint, perception capability constraint, radar detection constraint and public user communication quality constraint; the optimization problem is used to optimize the base station's transmit beamforming and the phase shift of the smart reflection surface to maximize the covert communication rate between the base station and the hidden user end.

[0306] The solving unit 122 is used to decouple the optimization problem into multiple sub-problems; use an alternating iterative optimization algorithm to solve each sub-problem to obtain communication beamforming parameters, synaesthesia beamforming parameters and an optimal phase shift.

[0307] The third sending unit 123 is used to send the communication beamforming parameters and the synaesthesia beamforming parameters to the base station, and send the optimal phase shift to the smart reflective surface.

[0308] Based on the covert communication device disclosed in the above embodiment of the present invention, the non-convex joint optimization problem is decomposed into three sub-problems of perception beamforming, communication beamforming and IRS phase shift, and solved by an iterative optimization algorithm, wherein the optimal phase shift of the intelligent reflection surface is solved by semidefinite relaxation method and Gaussian randomization, the communication beamforming is solved by penalty function method and Dinkelbach algorithm, and the synaesthesia beamforming is solved by cvx solver. In this scheme, an iterative optimization algorithm is proposed to optimize the transmission beamforming of the intelligent reflection surface and the base station respectively by jointly optimizing the phase shift matrix of the intelligent reflection surface, synaesthesia beamforming and communication beamforming, thereby achieving a higher covert transmission rate than the traditional scheme.

[0309] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can refer to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiment. The system and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without creative work.

[0310] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0311] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A covert communication method, characterized in that: Applied to a base station, the base station is respectively connected to a jammer, an intelligent reflective surface and a central controller in communication, the method comprising: Receiving communication beamforming parameters and synaesthesia beamforming parameters obtained by solving an optimization problem by a central controller; the optimization problem is used to optimize the transmit beamforming of the base station and the phase shift of the smart reflective surface to maximize the concealed communication rate between the base station and the concealed user terminal; For each time slot in the eavesdropper's service cycle, if the time slot is the first time slot, the known initial state information of the eavesdropper is used as the current state information; if the time slot is not the first time slot, the current state information is predicted based on the historical state information of the eavesdropper obtained in the previous time slot; Transmitting a first superposition signal including a perception signal and the current state information based on the synaesthesia beamforming parameter, so that the jammer sends a jamming signal to the eavesdropper after receiving the current state information; Based on the communication beamforming parameters, a first message signal to be sent to the hidden user terminal is sent to the smart reflecting surface, so that the smart reflecting surface sends the first message signal to the hidden user terminal based on an optimal phase shift; the optimal phase shift is obtained by the central controller by solving the optimization problem and sent to the smart reflecting surface; When a perception echo signal generated by the eavesdropper reflecting the perception signal is received, accurate state information of the eavesdropper is estimated based on the perception echo signal, and the accurate state information is used as historical state information for the next time slot.

2. The method according to claim 1, characterized in that When receiving the perception echo signal generated by the eavesdropper reflecting the perception signal, estimating and obtaining accurate status information of the eavesdropper based on the perception echo signal includes: When receiving a perception echo signal generated by the eavesdropper reflecting the perception signal, extracting relevant information of the eavesdropper from the perception echo signal; The accurate status information of the eavesdropper is obtained by utilizing the relevant information and a tracking model constructed based on the extended Kalman filter technology.

3. The method according to claim 1, characterized in that The method further comprises: If the sensing echo signal is not received, the current state information is used as the historical state information of the next time slot.

4. The method according to any one of claims 1 to 3, characterized in that: The method further comprises: If there is a first message signal to be sent to the hidden user end and a second message signal to be sent to the public user end, based on the communication beamforming parameters, a second superimposed signal including the first message signal and the second message signal is sent to the smart reflecting surface, so that the smart reflecting surface sends the second superimposed signal to the hidden user end and the public user end based on the optimal phase shift.

5. A covert communication method, characterized in that: Applied to a central controller, the central controller is respectively connected to a base station and an intelligent reflective surface for communication, the method comprising: According to the multiple constraints obtained in advance, a non-convex optimization problem is constructed; the constraints include: communication concealment constraint, perception concealment constraint, total power constraint, perception capability constraint, radar detection constraint and public user communication quality constraint; the optimization problem is used to optimize the transmit beamforming of the base station and the phase shift of the smart reflection surface to maximize the concealed communication rate between the base station and the concealed user terminal; Decoupling the optimization problem into multiple sub-problems; Using an alternating iterative optimization algorithm to solve each of the sub-problems, and obtain communication beamforming parameters, synaesthesia beamforming parameters and an optimal phase shift; The communication beamforming parameters and the synaesthesia beamforming parameters are sent to the base station, and the optimal phase shift is sent to the smart reflective surface.

6. A covert communication device, characterized in that: Applied to a base station, the base station is respectively connected to a jammer, an intelligent reflective surface and a central controller in communication, and the device comprises: A receiving unit, used to receive the communication beamforming parameters and the synaesthesia beamforming parameters obtained by solving the optimization problem by the central controller; the optimization problem is used to optimize the transmit beamforming of the base station and the phase shift of the smart reflective surface to maximize the concealed communication rate between the base station and the concealed user terminal; A prediction unit is used for predicting the current state information based on the known initial state information of the eavesdropper for each time slot in the eavesdropper's service period if the time slot is the first time slot, and predicting the current state information based on the historical state information of the eavesdropper obtained in the previous time slot if the time slot is not the first time slot; A first sending unit, configured to transmit a first superposition signal including a perception signal and the current state information based on the synaesthesia beamforming parameter, so that the jammer sends a jamming signal to the eavesdropper after receiving the current state information; A second sending unit is used to send a first message signal to be sent to the hidden user terminal to the smart reflecting surface based on the communication beamforming parameter, so that the smart reflecting surface sends the first message signal to the hidden user terminal based on an optimal phase shift; the optimal phase shift is obtained by the central controller by solving the optimization problem and sent to the smart reflecting surface; The sensing unit is configured to estimate accurate state information of the eavesdropper based on the sensing echo signal when receiving the sensing echo signal generated by the eavesdropper reflecting the sensing signal, and use the accurate state information as historical state information of the next time slot.

7. The device according to claim 6, characterized in that The sensing unit is specifically used for: When receiving a perception echo signal generated by the eavesdropper reflecting the perception signal, extracting relevant information of the eavesdropper from the perception echo signal; The accurate status information of the eavesdropper is obtained by utilizing the relevant information and a tracking model constructed based on the extended Kalman filter technology.

8. The device according to claim 6, characterized in that The sensing unit is further used for: If the sensing echo signal is not received, the current state information is used as the historical state information of the next time slot.

9. The device according to any one of claims 6 to 8, characterized in that: The second sending unit is further used for: If there is a first message signal to be sent to the hidden user end and a second message signal to be sent to the public user end, based on the communication beamforming parameters, a second superimposed signal including the first message signal and the second message signal is sent to the smart reflecting surface, so that the smart reflecting surface sends the second superimposed signal to the hidden user end and the public user end based on the optimal phase shift.

10. A covert communication device, characterized in that: Applied to a central controller, the central controller is respectively connected to a base station and an intelligent reflective surface for communication, and the device comprises: A construction unit is used to construct a non-convex optimization problem according to multiple constraints obtained by pre-analysis; the constraints include: communication concealment constraint, perception concealment constraint, total power constraint, perception capability constraint, radar detection constraint and public user communication quality constraint; the optimization problem is used to optimize the transmit beamforming of the base station and the phase shift of the smart reflection surface to maximize the concealed communication rate between the base station and the concealed user terminal; A solving unit, used for decoupling the optimization problem to obtain a plurality of sub-problems; solving each of the sub-problems using an alternating iterative optimization algorithm to obtain communication beamforming parameters, synaesthesia beamforming parameters and an optimal phase shift; The third sending unit is used to send the communication beamforming parameter and the synaesthesia beamforming parameter to the base station, and send the optimal phase shift to the smart reflection surface.

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