Transform domain covert communication method based on intelligent reflecting surface

Abstract

The embodiment of the invention discloses a transform domain covert communication method based on an intelligent reflecting surface, and relates to the technical field of safety communication. According to the method, the legal channel and the eavesdropping channel of the multi-participation weight fractional Fourier are reconstructed by optimizing the phase of the intelligent reflecting surface, so that the secrecy rate is maximized. Moreover, by taking a constellation diagram fuzzy error and a rotation error detected by an eavesdropping end as optimization targets, the error between a multi-participation weight score Fourier camouflaged constellation diagram reaching the eavesdropping end and an existing signal constellation diagram in the environment is minimum through alternate optimization of multi-participation weight score Fourier and intelligent reflecting surface control parameters, so that the accuracy of the constellation diagram is improved. Therefore, the camouflage effect is improved. Compared with the condition that the intelligent reflecting surface is not used, the secrecy rate of the communication system can be remarkably improved; and meanwhile, the bit error rate performance of a legal receiving end is improved, and the bit error rate performance of a malicious eavesdropping end is deteriorated. Therefore, the effects that the legal link performance can be guaranteed and the eavesdropping end is interfered are achieved.

Description

Technical Field

[0001] The present invention relates to the field of secure communication technology, and in particular to a transform domain covert communication method based on an intelligent reflection surface. Background Art

[0002] Due to its open nature, wireless signals are inevitably easily intercepted by malicious eavesdroppers. Through the detection and analysis of electromagnetic signals, the location information and data content of communication signals can be estimated and predicted, which poses a serious threat to communication security. In modern wireless communications, ensuring security has become a basic requirement. Whether in the civilian field or military applications, the transmission of large amounts of private or confidential information through wireless media requires extremely high security standards.

[0003] In order to improve the security of communication signals, secure communication methods such as cooperative relay, artificial noise-assisted communication and signal camouflage have been formed. Researchers have proposed a design method for relay weights and transmission power allocation using multiple cooperative relays; some researchers have also designed a method for protecting the transmitter from transmitting data to multiple legitimate users by using the optimal artificial noise power broadcast by a friendly jammer. However, since the covert communication method based on cooperative relay requires the use of third-party equipment as a relay node, its deployment scalability is relatively low. Although artificial noise can eliminate information leakage, it also reduces power utilization. Therefore, designing a communication method that can both guarantee the performance of legitimate links and interfere with the eavesdropping end is an important and urgent issue. Summary of the invention

[0004] The embodiment of the present invention provides a transform domain covert communication method based on an intelligent reflective surface, which can both ensure the performance of a legitimate link and generate interference to an eavesdropping end.

[0005] To achieve the above object, the embodiments of the present invention adopt the following technical solutions:

[0006] The original data of the transmitting end is used to generate a multi-participation weighted fractional Fourier signal, wherein the original data of the transmitting end is subjected to spread spectrum processing and then to MP-WFRFT modulation;

[0007] The multi-participation weight fractional Fourier signal is converted into a radio frequency signal and sent through a direct link and an intelligent reflection surface (IRS) link, wherein the intelligent reflection surface (IRS) link uses an optimized IRS channel reconstruction key parameter and uses a constellation map camouflage key parameter to camouflage the receiving end signal, so that the optimized constellation map camouflage key parameter does not affect the IRS channel.

[0008] Among them, the multi-participation weighted fractional Fourier signal obtained by MP-WFRFT modulation is x s , xl is the lth DFT transform of x0, x0 is the complex sequence before modulation, l=0,1,2,3,ω l The weighting coefficients include: ω0 to ω3;

[0009] α represents the transformation order, V represents the scale vector, k is an integer, J is an imaginary number, V = [MV, NV] = [m0, m1, m2, m3, n0, n1, n2, n3] is divided into m k and n k Two components; ω l The matrix form of (α,V) is W α,V , W α,V =ω0(α,V)I+ω1(α,V)F+ω2(α,V)C+ω3(α,V)CF, where F is the normalized Fourier matrix, I is the identity matrix, and C is the permutation matrix.

[0010] Fission characteristics of constellation diagram I TIME =ω0(α,V)x0+ω2(α,V)x2; Gaussian blur characteristic of constellation diagram I FREQ =ω1(α,V)x1+ω3(α,V)x3, X0 represents the original signal, Xi is the FFT transform of Xi-1, i is a positive integer and i>=2X3 represents…

[0011] The converting the multi-participation weight fractional Fourier signal into a radio frequency signal and sending it through a direct link and an intelligent reflecting surface (IRS) link comprises: pre-processing the multi-participation weight fractional Fourier signal to obtain a radio frequency signal x w , sending RF signals via direct link and intelligent reflecting surface (IRS) link w The preprocessing includes: shaping filtering, D / A conversion and up-conversion processing; the receivers receiving the signal through the direct link and the intelligent reflecting surface (IRS) link include: a legitimate receiving end and an eavesdropping end.

[0012] The signal received by the legal receiving end is y B and the eavesdropping end receives the signal y E ;

[0013] P A is the transmission power, x w Xs represents the RF signal after shaping filtering, D / A conversion, up-conversion and other processing, Θ is the IRS reflection beam forming vector, In Θ to are the diagonal elements, θ n is the phase shift of the nth IRS element, N is the total number of IRS units, β nrepresents the reflection coefficient, β n * is the optimal reflection coefficient, usually set to 1. B and n E They are: the mean at the legitimate receiving end and the eavesdropping end is zero and the variance is and Gaussian noise, H AB , H AE is the direct channel that constitutes the IRS reflection beamforming vector θ, where H AB is the direct channel at the legitimate receiving end, H AE is the direct channel at the eavesdropping end, H AI , H IB , H IE Each represents the fading coefficient vector between Alice, Bob and Eve and the IRS.

[0014] Further, the method of optimizing the key parameters of IRS channel reconstruction includes: AI ΘH IB With direct channel H AB Perform phase alignment; set the reflection channel H AI ΘH IE The direct channel H at the eavesdropping end AE In opposite phase.

[0015] The method of optimizing the key parameters of constellation map camouflage includes: obtaining the positions of 16 cluster centers in the constellation map, calculating the degree of dispersion between the data and the cluster centers in the 16 constellation point clusters, and then obtaining the blurriness parameter of the constellation map. QAM ; Get the center points of the two clusters at the bottom of the constellation diagram, then get the bottom vector and x-axis vector of the constellation diagram, and then use the phase angle of the obtained vector to get the rotation angle of the constellation diagram QAM .

[0016] The method also includes: a first optimization step: taking the maximum confidentiality rate as the optimization target of the reflected beam forming of the IRS; a second optimization step: optimizing the multi-participation weight fractional Fourier parameters according to the given IRS parameters after completing the optimization of the IRS; and then alternately executing the first optimization step and the second optimization step.

[0017] The transform domain covert communication method based on the intelligent reflective surface provided by the embodiment of the present invention reconstructs the legal channel and the eavesdropping channel of the multi-participation weight fractional Fourier by optimizing the phase of the intelligent reflective surface to maximize the confidentiality rate. In addition, this embodiment takes the fuzzy error and rotation error of the constellation diagram detected by the eavesdropping end as the optimization target, and through the alternating optimization of the multi-participation weight fractional Fourier and the intelligent reflective surface control parameters, the error between the multi-participation weight fractional Fourier camouflage constellation diagram reaching the eavesdropping end and the existing signal constellation diagram in the environment is minimized, thereby improving the camouflage effect. Compared with the case where the intelligent reflective surface is not used, this embodiment can significantly improve the confidentiality rate of the communication system; it also simultaneously achieves the improvement of the bit error rate performance of the legitimate receiving end and the deterioration of the bit error rate performance of the malicious eavesdropping end. Thereby achieving the effect of both ensuring the performance of the legitimate link and interfering with the eavesdropping end. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 A framework diagram of a multi-participation weighted fractional Fourier signal communication system based on an intelligent reflection surface provided in an embodiment of the present invention.

[0020] Figure 2 The blurriness parameter provided by the embodiment of the present invention QAM and the rotation parameter angle QAM Schematic diagram.

[0021] Figure 3 A rotation angle definition diagram provided by an embodiment of the present invention.

[0022] Figure 4 An optimization flow chart of a multi-participation weighted fractional Fourier signal communication system based on an intelligent reflection surface provided in an embodiment of the present invention.

[0023] Figure 5 A diagram showing how the confidentiality rate varies with power provided in an embodiment of the present invention.

[0024] Figure 6 A performance diagram of the receiver bit error rate with and without IRS provided in an embodiment of the present invention.

[0025] Figure 7 A schematic diagram of the constellation camouflage effect provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments of the present invention will be described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be interpreted as limiting the present invention. It can be understood by those skilled in the art that, unless specifically stated, the singular forms "one", "one", "said" and "the" used herein may also include plural forms. It should be further understood that the term "including" used in the specification of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or their groups. It should be understood that when we say that an element is "connected" or "coupled" to another element, it can be directly connected or coupled to other elements, or there may also be intermediate elements. In addition, the "connection" or "coupling" used here may include wireless connection or coupling. The term "and / or" used herein includes any unit and all combinations of one or more associated listed items. It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meaning as generally understood by those of ordinary skill in the art to which the present invention belongs. It should also be understood that terms such as those defined in general dictionaries should be understood to have meanings consistent with the meanings in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless defined as herein.

[0027] The embodiment of the present invention provides a transform domain covert communication method based on a smart reflective surface, comprising the following steps:

[0028] Step 1: Generate the initial multi-weighted fractional Fourier signal. Specifically, there are often various forms of interference such as signals and noise in the wireless environment. In particular, the target signal in the external environment has a constellation diagram that is exactly the same as the constellation diagram after MP-WFRFT disguise, which causes serious interference to the legitimate receiving end. Therefore, the anti-interference ability of the signal must be considered in the design of secure communication signals. This paper adopts spread spectrum anti-interference technology. First, the original data is spread spectrum processed at the transmitting end, and then, after QPSK mapping, serial-to-parallel conversion and other processes, the complex sequence x0 before modulation is obtained. Finally, x0 is modulated by MP-WFRFT. Since the four-term MP-WFRFT is the most widely used, the MP-WFRFT mentioned in this paper is the four-term MP-WFRFT. The modulated data x s for:

[0029]

[0030] Among them, x l is the lth DFT transform of x0, ω l is the weighting coefficient, l=0,1,2,3.

[0031] Weighting coefficient ω l is a function of the transformation order α and the scale vector V, and is defined as follows:

[0032]

[0033] Among them, the transformation order V=[MV,NV]=[m0,m1,m2,m3,n0,n1,n2,n3] represents the scale vector. When the exponential term is positive, the phase rotates counterclockwise around the origin. When the exponential term is negative, the phase rotates clockwise around the origin.

[0034] Express the above formula (2) in matrix form, then W α,V As shown in the following formula (3):

[0035]

[0036] Where F is the normalized Fourier matrix, I is the unit matrix, and C is the permutation matrix. By controlling parameters such as (α, m0, m1, m2, m3, n0, n1, n2, n3), the fuzzy, rotational, and split changes of the MP-WFRFT constellation can be achieved, and the constellation deception can be realized. ω0(α, V)x0 and ω2(α, V)x2 in formula (4) are the time domain components in the mixed carrier, and their synthetic terms determine the fission characteristics of the constellation.

[0037] I TIME =ω0(α,V)x0+ω2(α,V)x2 (4)

[0038] The configuration of the constellation after fission is determined by the relative relationship between ω0(α,V)x0 and ω2(α,V)x2. When ω0(α,V)⊥ω2(α,V), the angle between ω0 and ω2 is always around 90° or 270°. At this time, the constellation points after fission are rectangular. The rotation characteristics of the constellation are controlled by the angle value of ω2. In addition, the number of constellation points after the constellation fission and the distance between adjacent constellation points are controlled by μ=|ω0| / |ω2|. When μ takes different values, the constellation will be split into different numbers of points.

[0039] ω1(α, V)x1 and ω3(α, V)x3 are the frequency domain components in the mixed carrier, and their synthetic terms determine the Gaussian blur characteristics of the constellation diagram.

[0040] I FREQ=ω1(α,V)x1+ω3(α,V)x3 (5)

[0041] The noise-like component brought by the synthetic term in formula (5) can be regarded as artificial noise added to the signal. |ω1+ω3| determines the sum of the power of the noise-like components. For the legitimate sender and receiver, since the synthetic term of x1 and x3 can be completely restored and offset, it will not affect the final receiving performance; for the eavesdropper, if the accurate MP-WFRFT control parameters cannot be obtained, the synthetic term of x1 and x3 will be regarded as noise, which will seriously affect the channel estimation of the eavesdropper and cause the receiving performance of the eavesdropper to deteriorate.

[0042] Step 2: Transmitting the multi-weighted fractional Fourier signal through the direct channel (also called the direct link) and the reflection channel (also called the intelligent reflecting surface (IRS) link). The multi-weighted fractional Fourier signal with camouflage characteristics after MP-WFRFT modulation x s (This can be called a camouflage signal), which is processed by shaping filtering, D / A conversion, up-conversion, etc. to form a radio frequency signal x w , respectively through direct links

[0043] The legal receiver of the IRS-Assisted MP-WFRFT system receives the signal y B and the eavesdropping end receives the signal y E Respectively expressed as:

[0044]

[0045] Among them, P A is the transmission power, is a diagonal matrix whose diagonal elements are the IRS reflection coefficient matrix, θ n is the phase shift of the nth IRS element, N is the total number of IRS units,

[0046] θ n ∈[0,2π]n=1,2,…N,β n * is the optimal reflection coefficient, usually set to β n * =1. B and n E The mean is zero at the legal receiving end and the variance is and Gaussian noise.

[0047] Step 3: Define the key parameters of IRS channel reconstruction. In secure communication, the confidentiality rate between the legitimate receiving end Bob and the eavesdropping end Eve is often used to measure the effect of secure communication. The confidentiality rate can be defined as:

[0048] R cov =max(0,R B -R E )(8)

[0049] Among them, R B and R E They represent the achievable rates of the legitimate link and the eavesdropping link respectively, and the expressions are as follows:

[0050]

[0051] In order to maximize the confidentiality rate R cov , the direct channel H that constitutes the IRS reflection beamforming vector Θ needs to be AB , H AE and reflection channel H AI ΘH IB , H AI ΘH IE The optimization strategy for the legal channel is to maximize the signal power received at Bob and the reflection channel H AI ΘH IB Need to communicate with direct channel H AB phase alignment to maximize R B The optimization strategy of the eavesdropping channel is to minimize the signal power received at Eve and the reflection channel H AI ΘH IE Direct channel H with Eve AE should be in opposite phase to cancel the signal and achieve R E Generally speaking, when designing the IRS phase, it is necessary to balance the above two objectives.

[0052] Step 4: Define the key parameters of constellation camouflage. The distribution structure of constellation points, the degree of fuzziness of constellation points and the rotation angle of constellation are important criteria for evaluating the effect of constellation camouflage. The MP-WFRFT signal reaches the receiver through the direct link and the IRS reflection link respectively. The two signals are superimposed in amplitude and phase, and the composite constellation shows random characteristics, which cannot achieve the effect of constellation camouflage. Since the distribution structure of constellation points is uniquely determined by the MP-WFRFT parameters and is not affected by the two links, this paper selects the fuzzy parameter blurriness. QAM and the rotation parameter angle QAM As a key parameter, the constellation diagram of the composite signal is camouflaged.QAM and angle QAM Principle as attached Figure 2 shown.

[0053] To extract the fuzzy parameters of the constellation diagram, first, we need to calculate the positions of the 16 cluster centers in the 16QAM constellation diagram. This paper uses the K-means algorithm for cluster analysis. Then, we calculate the degree of dispersion between the data and the cluster centers in the 16 constellation point clusters. Finally, we calculate the fuzzy parameter blurriness of the constellation diagram. QAM .

[0054] The specific process is as follows:

[0055] 1. Divide the 16QAM constellation into 16 clusters

[0056] First, the constellation data is divided into 16 groups, 16 data points are randomly selected as the initial cluster centers, the distance between each data point and each seed cluster center is calculated, and each data point is assigned to the cluster center closest to it. Each time a data point is assigned, the cluster center of the cluster will be recalculated according to the existing objects in the cluster. This process will be repeated until the cluster center no longer changes and the error square sum is locally minimized. Finally, 16 clusters Λ are obtained, and the data set of a cluster is represented as Λ(j), j=1,2,…16.

[0057] 2. Calculate the average variance of the 16 clusters

[0058] In a constellation diagram, the degree of dispersion can usually be measured by calculating the variance of the constellation points. Variance is a statistical indicator that measures the degree of data dispersion. For a constellation diagram, the variance of the in-phase component and the orthogonal component can be calculated separately. Select a cluster Λ(j), and the data points in the cluster are represented by z1, z2, …, z m , m is the number of data points in the cluster. i There is an in-phase component real(z i ) and the orthogonal component imag(z i ), calculate the variance Var of its two components real (j) and Var imag (j):

[0059]

[0060] Among them, mean real and mean imag are the means of the in-phase and quadrature components, respectively.

[0061] Then, the average of the 16 clusters is taken to obtain the variance Var of the in-phase component of the constellation diagram. real and the orthogonal component variance Var imag :

[0062]

[0063] 3. Obtain fuzzy parameter indicators

[0064] Add the variance of the in-phase component and the variance of the orthogonal component to get the comprehensive fuzzy parameter index blurriness QAM :

[0065] blurriness QAM =Var real +Var imag (15)

[0066] To extract the rotation parameters of the constellation diagram, first, calculate the center points of the two clusters at the bottom of the constellation diagram, then obtain the bottom vector and the x-axis vector of the constellation diagram, and specify the rotation direction, and then use the phase angle of these two vectors to obtain the rotation angle of the constellation diagram using the arc cosine function. QAM The specific process is as follows:

[0067] 1. Obtaining the center point of the bottom edge cluster

[0068] As attached Figure 3 As shown, the center points of the four clusters at the bottom of the constellation diagram are selected to form vector B. To simplify the problem, the center of the first cluster Λ(1) (mean(1) real ,mean(1) imag ) points to the center point (mean(4) of the fourth cluster Λ(4) real ,mean(4) imag ) form vector B.

[0069] 2. Vector selection and definition

[0070] First, define vector A = [1,0], and assume that vector B always points from left to right. When the second component B(2) of vector B is positive, the constellation diagram is defined to rotate counterclockwise, with an angle range of 0-45°; when the second component of vector B is negative, the constellation diagram is defined to rotate clockwise, with an angle mapping of 45°-90°, which is equal to Figure 4 The angle formed by the dotted lines in (b). The B vector is:

[0071] B=(mean(4) real -mean(1) real ,mean(4) imag -mean(1) real )(16)

[0072] 3. Get the rotation parameter index

[0073] Calculate the phase angle angle between vectors A and B AB :

[0074]

[0075] Wherein, acos is the arc cosine function.

[0076] So, the rotation angle is angle QAM for:

[0077] angle QAM =mod(sign(B(2))×angle AB +90,90)(18)

[0078] Where mod is the modulus operator and sign is the sign function.

[0079] Obtaining the blurriness parameter of the external target signal constellation diagram QAM and the rotation parameter angle QAM After that, the MP-WFRFT signal after the two links are combined can be compared with the external target signal in constellation diagram, and the fuzzy error and rotation error of the constellation diagrams of the two can be used as the optimization target of constellation diagram camouflage.

[0080] Step 5: Optimizing IRS under given multi-participation weighted fractional Fourier parameters. In order to improve the concealment performance of the IRS-assisted MP-WFRFT system, we take the maximum confidentiality rate as the optimization goal of the IRS reflection beamforming. Considering the IRS optimization strategies of the legitimate channel and the eavesdropping channel, the mathematical model of the IRS reflection beam optimization problem can be expressed as:

[0081]

[0082] Among them, P A is the transmission power, n B and n E The variances of the zero-mean Gaussian noise at the legitimate receiving end and the malicious eavesdropping end are and but:

[0083]

[0084] Introducing variable H B and H E :

[0085] H B =η B ·H AB ·H AB * (twenty two)

[0086] H E =η E ·H AE ·H AE * (twenty three)

[0087] Then the mathematical model of formula (19a) can be transformed into:

[0088]

[0089] Further, three intermediate parameters Γ are set B , Γ E and r is:

[0090] Γ B =diag(H IB )H AI (25)

[0091] Γ E =diag(H IE )H AI (26)

[0092] r=[θ1,...,θ N ] H (27)

[0093] but:

[0094] H IB ΘH AI =r H Γ B (28)

[0095] H IE ΘH AI =r H Γ E (29)

[0096] In order to further simplify the optimization model, the intermediate parameters are introduced and

[0097]

[0098] make

[0099]

[0100] rank(R)=1 (34)

[0101] Substituting (30)-(32) into the optimization model (24), the optimization model can be simplified as:

[0102]

[0103] sqF n,n =1,n=1,...,N+1, (35b)

[0104] R≥0,(35c)

[0105] rank(R)=1. (35d)

[0106] From the above derivation, we can see that we transform the optimization model into an SDP problem through the SDR technique, but (35) does not always produce a rank-1 solution. So we will delete the rank-1 constraint and introduce the auxiliary variable And K = λR, Then, by applying the Charnes-Cooper transformation, the optimization problem (35) can be simplified to:

[0107]

[0108] tr(IK)=λ,R≥0, (36c)

[0109] λ≥0,K≥0. (36d)

[0110] Among them, λ, K, and R represent three custom variables. K = λR,

[0111] Therefore, we can apply the Gaussian randomization method to obtain an approximate first-order solution from the high-order solutions of problem (36), which is the maximum confidentiality rate of the IRS-assisted MP-WFRFT system.

[0112] Step 6: Optimize the multi-participation weight fractional Fourier parameters under given IRS parameters. Based on the maximum confidentiality rate obtained by reconstructing the channel through IRS in step 5, the legal receiver extracts the blurriness of the external 16QAM signal according to formulas (15) and (18): QAM and the rotation error angle QAM In addition, the legitimate receiver sends the above error parameters to the transmitter Alice through the communication link. Then, Alice performs constellation camouflage design for the nine control parameters of MP-WFRFT (α, m0, m1, m2, m3, n0, n1, n2, n3), so that the composite constellation reaching the receiver through the two links is minimally different from the constellation of the external target signal.

[0113] First, the MP-WFRFT optimization model is constrained according to the characteristics of the constellation diagram. This paper selects the 16QAM signal commonly used in WFRFT research as the disguised target signal and the QPSK signal as the original signal. In order to satisfy the rectangular structure invariance of the signal constellation diagram after passing through the channel, we hope that <ω0,ω2> approaches 90°. Approaching 0. At the same time, we hope that the 16 point clusters of the 16QAM constellation diagram are evenly distributed. μ=0.5. In addition, the scale vector V is a non-negative integer, the upper limit of the value is set to 10, and the value range of the transformation order α is set to [0,4). Therefore, the optimization model can be established as follows:

[0114]

[0115] Where ω is the weighting coefficient, l = 0, 1, 2, 3; Δangle represents the angle difference, and Δblurriness represents the difference in blurriness. Indicates the rotation angle of the EVE constellation diagram. Indicates the fuzziness of the constellation diagram on the EVE side, and i represents an imaginary number.

[0116] According to the above optimization model, this embodiment uses a genetic algorithm GA to iteratively optimize α and V of MP-WFRFT to obtain the optimal parameter set for this optimization.

[0117] Step 7: In order to obtain the best IRS channel reconstruction and composite constellation camouflage effect, this paper alternately optimizes the IRS optimization in step 5 and the MP-WFRFT optimization in step 6. The optimization flow chart is as follows Figure 4 shown.

[0118] Step 8: Simulate and verify the proposed embodiment. Assume that Alice, IRS, Bob, and EVE are located at (0, 0), (130, 5), (135, 0), and (130, -5) in the two-dimensional plane, respectively (in meters). In the channel modeling part, we use H AI , H IB , H IE , H AB and H AE Modeled as a fading channel, the path loss at the reference distance of 1m is set to -30dB, and the path loss exponent is set to 3. The camouflaged target signal is selected as the 16QAM signal commonly used in WFRFT research, and the original signal is selected as the QPSK signal. The accuracy of the IRS optimization algorithm in Part IV C is set to 10 -3 , take the average value of 1000 random fadings. Figure 5,6,7 It can be seen that this embodiment greatly improves the confidentiality capacity of the system and realizes the optimization of the constellation diagram. At the same time, it also reduces the bit error rate at the legitimate receiving end and improves the bit error rate at the eavesdropping end.

[0119] This embodiment takes the MP-WFRFT camouflage signal as the object and constructs an IRS-assisted system model. On the one hand, the channel reconstruction capability of IRS is used to cancel the reflected signal and the direct signal at the eavesdropping end, thereby concealing the communication process from the eavesdropping end; on the other hand, the editing function of MP-WFRFT on the time-frequency characteristics of the signal is used to achieve the camouflage of the signal modulation constellation characteristics. In view of the security issues of the communication process, this embodiment proposes an optimization scheme for IRS reflection beamforming based on MP-WFRFT signals. In order to solve the non-convex optimization problem of the optimization model, an efficient approximate solution algorithm based on semidefinite relaxation (SDR) and Gaussian randomization method is adopted to maximize the confidentiality rate of the legitimate receiving end and the malicious eavesdropping end. The MP-WFRFT system assisted by the intelligent reflecting surface has two links, direct and IRS reflection, and the camouflage effect of the constellation diagram of the receiving end is jointly determined by the signals of the two links. The traditional MP-WFRFT constellation diagram editing method cannot achieve the camouflage design of the two links. To address the above problems, this embodiment takes the fuzzy error and rotation error of the camouflaged constellation diagram at the receiving end as the optimization target, establishes a control parameter feedback adjustment mechanism, and minimizes the difference in the constellation diagram between the MP-WFRFT camouflaged signal of the two links and the external signal through alternating optimization of the MP-WFRFT and IRS control parameters, thereby achieving the best constellation diagram camouflage effect.

[0120] Compared with the case where IRS is not used, the proposed method of this embodiment can significantly improve the confidentiality rate of the communication system; the proposed method simultaneously improves the bit error rate performance of the legitimate receiving end and deteriorates the bit error rate performance of the malicious eavesdropping end. Under the condition of IRS, as the transmission power increases, the bit error rate of the legitimate receiver decreases significantly (when the transmission power is 15dBm, the bit error rate decreases from 10 -0.8 Reduced to 10 -2.9 ), the bit error rate of the malicious eavesdropping end is relatively high (when the transmission power is 15dBm, the bit error rate increases from 10 -0.4 Increase to 10 -0.3 ) and maintained at 10 -0.3 At the same time, the constellation map camouflage and confidentiality capacity are also improved.

[0121] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The above is only a specific implementation method of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or replacements that can be easily thought of by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A transform domain covert communication method based on smart reflective surface, characterized in that: include: The original data of the transmitting end is used to generate a multi-participation weighted fractional Fourier signal, wherein the original data of the transmitting end is subjected to spread spectrum processing and then to MP-WFRFT modulation; Convert the multi-weighted fractional Fourier signal into a radio frequency signal and send it through a direct link and an intelligent reflecting surface (IRS) link; 2. The method according to claim 1, characterized in that The multi-weighted fractional Fourier signal obtained by MP-WFRFT modulation is x s , x l is the lth DFT transform of x0, x0 is the complex sequence before modulation, l=0,1,2,3,ω l The weighting coefficients include: ω0 to ω3; in, α represents the transformation order, V represents the scale vector, k is an integer, j represents an imaginary number, and m k and n k represents the first component and the second component; ω l The matrix form of (α,V) is W α,V , W α,V =ω0(α,V)I+ω1(α,V)F+ω2(α,V)C+ω3(α,V)CF, where F is the normalized Fourier matrix, I is the identity matrix, and C is the permutation matrix.

3. The method according to claim 2, characterized in that Fission characteristics of constellation diagrams I TIME =ω0(α,V)x0+ω2(α,V)x2; Gaussian Blur Characteristics of Constellation Diagrams I FREQ =ω1(α,V)x1+ω3(α,V)x3, X0 represents the original signal, Xi is the FFT transform of Xi-1, i is a positive integer and i>=2X3 represents… 4. The method according to claim 1, characterized in that: The converting the multi-participation weighted fractional Fourier signal into a radio frequency signal and sending the signal through a direct link and an intelligent reflecting surface (IRS) link comprises: The multi-weighted fractional Fourier signal is preprocessed to obtain the radio frequency signal x w , sending RF signals via direct link and intelligent reflecting surface (IRS) link w , the pre-processing includes: shaping filtering, D / A conversion and up-conversion processing; The receivers that receive signals through direct links and intelligent reflecting surface (IRS) links include: legitimate receivers and eavesdroppers.

5. The method according to claim 1 or 4, characterized in that: The signal received by the legal receiving end is y B and the eavesdropping end receives the signal y E ; P A is the transmission power, X w represents the RF signal corresponding to Xs, Θ is the IRS reflection beamforming vector, In Θ to are the diagonal elements, θ n is the phase shift of the nth IRS element, N is the total number of IRS units, β n represents the reflection coefficient, β n * is the optimal reflection coefficient, n B and n E They are: the mean at the legitimate receiving end and the eavesdropping end is zero and the variance is and Gaussian noise, H AB , H AE is the direct channel that constitutes the IRS reflection beamforming vector θ, where H AB is the direct channel at the legitimate receiving end, H AE is the direct channel at the eavesdropping end, H AI , H IB , H IE Each represents the fading coefficient vector between Alice, Bob and Eve and the IRS.

6. The method according to claim 1, characterized in that Methods for optimizing key parameters of IRS channel reconstruction include: The reflection channel H AI ΘH IB With direct channel H AB Perform phase alignment; The reflection channel H AI ΘH IE The direct channel H at the eavesdropping end AE In opposite phase.

7. The method according to claim 1, characterized in that Ways to optimize the key parameters of constellation camouflage include: Get the positions of the 16 cluster centers in the constellation map, calculate the discrete degree of the data and the cluster centers in the 16 constellation point clusters, and then get the blurriness parameter of the constellation map QAM ; Get the center points of the two clusters at the bottom of the constellation diagram, then get the bottom vector and x-axis vector of the constellation diagram, and then use the phase angle of the obtained vector to get the rotation angle of the constellation diagram QAM .

8. The method according to claim 1, characterized in that Also includes: The first optimization step: maximizing the confidentiality rate is used as the optimization goal of the IRS reflection beamforming.

9. The method according to claim 8, characterized in that Also includes: The second optimization step: after completing the optimization of IRS, the multi-participation weight fractional Fourier parameters are optimized according to the given IRS parameters; Then, the first optimization step and the second optimization step are performed alternately.

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