RIS-assisted cognitive radio wireless secure communication transmission method using partial CSI

Abstract

The present invention proposes a RIS-assisted cognitive radio wireless security communication transmission method using partial CSI. In the RIS-assisted large-scale multi-input multi-output cognitive radio wireless security communication system, in order to enable the secondary transmitter and the secondary user to communicate with the main transmitter and the main user in the same frequency band, and to ensure that the interference of the secondary transmitter to the main user is within a certain threshold, the initial value of the RIS reflection coefficient matrix is ​​set, and the beamforming matrix is ​​designed using the partial CSI; the RIS reflection coefficient matrix is ​​designed using the partial CSI according to the beamforming matrix; the above operations are repeated until the system security rate converges. The present invention can effectively improve the spectrum efficiency under the premise of knowing the partial CSI, alleviate the spectrum scarcity problem in actual communication scenarios, and improve the security rate of the system.

Description

Technical Field

[0001] The present invention belongs to the field of Internet of Things (IoT), and in particular to a reconfigurable intelligent reflection surface (RIS) assisted cognitive radio secure communication transmission method using partial channel state information (Channel State Information, CSI) of legitimate users. Background Art

[0002] At present, IoT has been gradually applied to various fields, such as industry, agriculture, medicine, etc. Billions of IoT devices are distributed everywhere. Such a large number of IoT users, a large amount of valuable data, and IoT devices with limited energy have brought huge challenges to the current communication network. On the one hand, due to the broadcast nature of wireless media, IoT networks are easily eavesdropped. Physical layer security has become a very valuable technology to ensure secure communications. RIS has been applied to physical layer security because it shows great potential in improving IoT secure communication performance by controlling the propagation environment.

[0003] On the other hand, with the increasing popularity of IoT devices, the data traffic of mobile communications has grown exponentially in recent years. According to data, the number of handheld mobile devices is expected to reach 17.72 billion by the end of 2024. Spectrum has become a very scarce resource, which has prompted researchers to study the mechanism of providing spectrum efficiency. The concept of cognitive radio has been proposed and regarded as one of the most effective technologies to improve spectrum efficiency. Cognitive radio is an environment-aware intelligent wireless system that uses spectrum sensing and sharing technology to effectively alleviate the scarcity of spectrum resources caused by the growth of wireless devices.

[0004] The present invention proposes a RIS-assisted cognitive radio wireless secure communication transmission method using partial CSI. The difficulty lies in that in a downlink MIMO cognitive radio communication system, in order to ensure that the secondary transmitter and the secondary user can communicate with the primary transmitter and the primary user in the same frequency band, the optimization of the system security rate needs to be based on the premise that the interference of the secondary transmitter to the primary user is within a certain threshold. Summary of the invention

[0005] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art and provide a RIS-assisted cognitive radio wireless security communication transmission method using partial CSI. Under the condition of ensuring that the interference of the secondary transmitter to the primary user is within a certain threshold, the system security rate is maximized, and the beamforming matrix and the RIS reflection coefficient matrix are designed using partial CSI to maximize the system security rate.

[0006] The present invention provides a RIS-assisted cognitive radio secure communication transmission method using partial CSI, comprising the following steps:

[0007] S1. Construct a RIS-assisted cognitive radio wireless secure communication transmission system applicable to partially known CSI; the system includes a main transmitter, a main user with M antennas, a secondary transmitter with D antennas, a secondary user with N antennas, an eavesdropper with E antennas, and a RIS integrating L low-power reflection units;

[0008] S2. In the RIS-assisted massive MIMO cognitive radio wireless security communication system, in order to enable the secondary transmitter and the secondary user to communicate with the primary transmitter and the primary user in the same frequency band and ensure that the interference of the secondary transmitter to the primary user is within a certain threshold, the initial value of the RIS reflection coefficient matrix is ​​set;

[0009] S3, using part of the CSI, designing a beamforming matrix;

[0010] S4. Design a RIS reflection coefficient matrix based on the beamforming matrix and using part of the CSI.

[0011] S5. Repeat steps S3 and S4 until the system safety rate converges.

[0012] In the RIS-assisted large-scale multi-input multi-output cognitive radio wireless security communication system, the present invention sets the initial value of the RIS reflection coefficient matrix, uses part of the CSI to design the beamforming matrix, and uses part of the CSI to design the RIS reflection coefficient matrix in order to enable the secondary transmitter and the secondary user to communicate with the main transmitter and the main user in the same frequency band, and ensure that the interference of the secondary transmitter to the main user is within a certain threshold. According to the beamforming matrix, the RIS reflection coefficient matrix is ​​designed using part of the CSI; and the above operations are repeated until the system security rate converges. The present invention can effectively improve the spectrum efficiency under the premise of knowing part of the CSI, alleviate the problem of spectrum scarcity in actual communication scenarios, and improve the security rate of the system.

[0013] The technical solution further optimized by the present invention is as follows:

[0014] In step S1, the direct link between the secondary transmitter and the secondary user and the eavesdropper is blocked by an obstacle, and there is only one reflection path through RIS between the secondary transmitter and the secondary user and the eavesdropper, and the channels H from the secondary transmitter to RIS, RIS to the primary user, RIS to the secondary user, and RIS to the eavesdropper are t They are:

[0015]

[0016] in, represents the deterministic line-of-sight component of the channel, represents the non-line-of-sight component of the channel and R t represents the spatial correlation matrix of the receiving antenna, T t represents the spatial correlation matrix of the transmit antenna, and R a , R P , R b , R e 、T a 、T P 、T b 、T e , are deterministic non-negative matrices of dimensions L×L, D×D, N×N, E×E, M×M, L×L, L×L, L×L, L×M, N×L, E×L, and D×L, respectively, representing part of the CSI including large-scale fading and Ricean factors; X t is composed of the random components of the channel, and X a , X P , X b , X e They are L×M, N×L, E×L, and D×L matrices, respectively, where the elements are independent and identically distributed with zero mean and unit variance; represents the square root of the matrix; the transmitted signal s is an M×1 column vector, and the beamforming matrix Q=E{ss H},(·) H represents the conjugate transpose of the matrix. The RIS reflection coefficient matrix Φ is a L×L diagonal matrix and Φ=diag([θ1,θ2,...θ l ...,θ L ] T ), θ l is the reflection coefficient and j is the imaginary unit, Indicates the adjustment angle of RIS to the signal and

[0017] In step S2, an initial RIS reflection coefficient matrix Φ=I is given. L , where I L is the L×L identity matrix.

[0018] In step S3, designing a beamforming matrix using part of the CSI includes the following steps:

[0019] Beamforming Matrix Q * for:

[0020]

[0021] Among them, K and Λ Q is an auxiliary variable, and its expression is as follows:

[0022]

[0023]

[0024] Among them, max{a,b} means taking the larger number between a and b. is the Taylor expansion center, V K and Λ K All through Perform eigenvalue decomposition The obtained auxiliary variable, F b and F e is an auxiliary variable, and its specific expression is as follows:

[0025]

[0026]

[0027] v is Q * Meet trQ * ≤MP T , tr(·) represents the trace of the matrix, P T is the total transmitted power, λ is the * Satisfy the interference power constraint E{tr(H P ΦH a Q * (H P ΦH a ) H )}≤MP I , E{·} represents the expectation of the matrix, and the specific expression is:

[0028]

[0029] P I is the maximum interference power threshold at the primary user; I M is the M×M identity matrix, It is an equivalent channel parameter based on the system partial CSI, and its specific expression is as follows:

[0030]

[0031]

[0032]

[0033]

[0034]

[0035]

[0036]

[0037]

[0038] Among them, F i , Θ i ,Ξ b ,Ξ e ,Ψ i , Π i , Γ i They are all auxiliary variables and i∈{b,e}. The specific expressions are as follows:

[0039]

[0040] Θ i =I L +i1Ψ i R a

[0041] Ξ b =σ 2 I N +b2R b

[0042] Ξ e =σ 2 I E +e2R e

[0043]

[0044]

[0045]

[0046] In the formula, is the and is the and i1 is b1 and e1 in the above expression, σ 2 is the variance of Gaussian white noise with mean 0, I N is the N×N identity matrix, I E is the E×E identity matrix, and the optimal beamforming matrix Q is obtained opt =Q * .

[0047] In step S4, according to the beamforming matrix, using part of the CSI, the RIS reflection coefficient matrix is ​​designed, which specifically includes the following steps:

[0048] S401, taking the projection gradient parameter μ=0.5, calculating the Lagrangian function of the rate with respect to the interference power constraint The specific expression is as follows:

[0049]

[0050] In the formula, Indicates the system safety rate, as follows:

[0051]

[0052] Where A is the Lagrange multiplier.

[0053] S402, update the projection gradient parameter μ * :

[0054]

[0055] Wherein, Δ is the step size, and Δ=0.1 is taken.

[0056] S403, Order Calculate the phase parameter θ of the RIS reflection coefficient matrix * ,in yes About θ l The derivative of , for any l=1,2,...,L, is:

[0057]

[0058] Among them, E ll is a matrix in which all values ​​are 0 except the value of the lth row and lth column, which is 1; b and e It is an auxiliary function, and its specific expression is as follows:

[0059]

[0060]

[0061] S404, RIS reflection coefficient matrix Φ * =diag(θ * ), and obtain the optimal RIS reflection coefficient matrix Φ opt =Φ * .

[0062] In step S5, steps S3 and S4 are repeated until the system safety rate is Convergence, where The specific expression of is shown in step S4, and the optimal system safety rate is obtained.

[0063] Compared with the prior art, the present invention adopts the above technical solution and has the following technical effects:

[0064] (1) The present invention is more practical, that is, it adopts partial CSI, alternately optimizes the beamforming matrix and the RIS reflection coefficient matrix, and is easier to obtain than instantaneous CSI;

[0065] (2) The present invention adopts cognitive radio technology and utilizes spectrum sensing and sharing to improve the safe rate of the system while ensuring that the interference of secondary transmitters to primary users is within a certain threshold, thereby alleviating the problem of the growth of wireless devices and the scarcity of spectrum resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 It is a flow chart of the present invention.

[0067] Figure 2 Schematic diagram of the system in the present invention. DETAILED DESCRIPTION

[0068] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings: This embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation method and specific operation process are given, but the protection authority of the present invention is not limited to the following embodiments.

[0069] This embodiment proposes a RIS-assisted cognitive radio wireless secure communication transmission method using partial CSI, under the condition that the interference of the secondary transmitter to the primary user is within a certain threshold, with the goal of maximizing the system security rate, using partial CSI to design the beamforming matrix and the RIS reflection coefficient matrix to maximize the system security rate. Figure 1 As shown, the specific steps include:

[0070] Step 1: construct a RIS-assisted cognitive radio wireless secure communication transmission system applicable to partially known CSI; the system includes a main transmitter (omitted in the figure), a main user with M antennas, a secondary transmitter with D antennas, a secondary user with N antennas, an eavesdropper with E antennas, and a RIS integrating L low-power reflection units;

[0071] Step 1.1: The direct links between the secondary transmitter and the secondary user and the eavesdropper are blocked by obstacles. There is only one reflection path through RIS between the secondary transmitter and the secondary user and the eavesdropper. The channels H from the secondary transmitter to RIS, RIS to the primary user, RIS to the secondary user, and RIS to the eavesdropper are t They are:

[0072]

[0073] Right now:

[0074]

[0075]

[0076]

[0077] Among them, H a represents the channel from the secondary transmitter to the RIS, H P represents the channel from RIS to the primary user, H b represents the channel from RIS to secondary users, H e It represents the channel from RIS to the eavesdropper; represents the deterministic line-of-sight component of the channel, i.e. represents the deterministic line-of-sight component of the secondary transmitter-to-RIS channel, represents the deterministic line-of-sight component of the channel from the RIS to the primary user, represents the deterministic line-of-sight component of the channel from the RIS to the secondary user, represents the deterministic line-of-sight component of the channel from RIS to the eavesdropper; represents the non-line-of-sight component of the channel and Right now represents the non-line-of-sight component of the channel from the secondary transmitter to the RIS, represents the non-line-of-sight component of the channel from RIS to the primary user, represents the non-line-of-sight component of the channel from RIS to the secondary user, represents the non-line-of-sight component of the channel from RIS to the eavesdropper; R t represents the spatial correlation matrix of the receiving antenna, T t represents the spatial correlation matrix of the transmitting antenna, and R a , R P , R b , R e , T a , T P , T b , T e , are deterministic non-negative matrices of dimensions L×L, D×D, N×N, E×E, M×M, L×L, L×L, L×L, L×M, N×L, E×L, and D×L, respectively, representing part of the CSI including large-scale fading and Ricean factors; X t is composed of the random components of the channel, and X a , X P , X b , X eare matrices of dimensions L×M, N×L, E×L, and D×L, respectively, where the elements are independent and identically distributed with zero mean and unit variance; represents the square root of the matrix; the transmitted signal s is an M×1 column vector, and the beamforming matrix Q=E{ss H},(·) H represents the conjugate transpose of the matrix; the RIS reflection coefficient matrix Φ is a L×L diagonal matrix and Φ=diag([θ1,θ2,...θ l ...,θ L ] T ), θ l is the reflection coefficient and j is the imaginary unit, Indicates the adjustment angle of RIS to the signal and

[0078] Step 1.2: In the RIS-assisted massive MIMO cognitive radio wireless security communication system, in order to enable the secondary transmitter and the secondary user to communicate with the primary transmitter and the primary user in the same frequency band and ensure that the interference of the secondary transmitter to the primary user is within a certain threshold, the initial value of the RIS reflection coefficient matrix is ​​set, and the beamforming matrix is ​​designed using part of the CSI, including the following steps:

[0079] Given the initial RIS reflection coefficient matrix Φ = I L , where I L is the L×L identity matrix; design the beamforming matrix Q * for:

[0080]

[0081] Among them, K and Λ Q is an auxiliary variable, and its expression is as follows:

[0082]

[0083]

[0084] Among them, max{a,b} means taking the larger number between a and b. is the Taylor expansion center, V K and Λ K All through Perform eigenvalue decomposition The obtained auxiliary variable, F b and F e is an auxiliary variable, and its specific expression is as follows:

[0085]

[0086]

[0087] v is Q * Meet trQ * ≤MP T , tr(·) represents the trace of the matrix, P T is the total transmitted power, λ is the * Satisfy the interference power constraint E{tr(H P ΦH a Q * (H P ΦH a ) H )}≤MP I , E{·} represents the expectation of the matrix, and the specific expression is:

[0088]

[0089] P I is the maximum interference power threshold at the primary user. M is the M×M identity matrix, It is an equivalent channel parameter based on the system partial CSI, and its specific expression is as follows:

[0090]

[0091]

[0092]

[0093]

[0094]

[0095]

[0096]

[0097]

[0098] Among them, F b , F e , Θ b , Θ e ,Ξ b ,Ξ e ,Ψ b ,Ψ e , Π b , Π e , Γ b , Γ e They are all auxiliary variables, and the specific expressions are as follows:

[0099]

[0100]

[0101] Θ b =I L +i1Ψ b R a

[0102] Θ e =I L +i1Ψ e R a

[0103] Ξ b =σ 2 I N +b2R b

[0104] Ξ e =σ 2 I E +e2R e

[0105]

[0106]

[0107]

[0108]

[0109]

[0110]

[0111] In the formula, is the and is the and i1 is b1 and e1 in the above expression, σ 2 is the variance of Gaussian white noise with mean 0, I N is the N×N identity matrix, I E is the E×E identity matrix, and the optimal beamforming matrix Q is obtained opt =Q * .

[0112] Step 2: Based on the beamforming matrix and using part of the CSI, the RIS reflection coefficient matrix is ​​designed, which specifically includes the following steps:

[0113] Step 2.1: Take the projection gradient parameter μ = 0.5 and calculate the Lagrangian function of the rate with respect to the interference power constraint The specific expression is as follows:

[0114]

[0115] In the formula, Indicates the system safety rate, as follows:

[0116]

[0117] Where A is the Lagrange multiplier.

[0118] Step 2.2: Update the projected gradient parameter μ * :

[0119]

[0120] Wherein, Δ is the step size, and Δ=0.1 is taken.

[0121] S403, Order Calculate the phase parameter θ of the RIS reflection coefficient matrix * ,in yes About θ l The derivative of , for any l=1,2,...,L, is:

[0122]

[0123] Among them, E ll is a matrix in which all values ​​are 0 except the value of the lth row and lth column, which is 1; b and e It is an auxiliary function, and its specific expression is as follows:

[0124]

[0125]

[0126] Step 2.4: RIS reflection coefficient matrix Φ * =diag(θ * ), and obtain the optimal RIS reflection coefficient matrix Φ opt =Φ * .

[0127] Step 2.5: Repeat steps 1.2 and 2.1 in step 2 until the system reaches a safe rate Convergence, where The specific expression of is shown in step 2.1, and the optimal system safety rate is obtained.

[0128] The above description is only a specific implementation of the present invention, but the protection scope of the present invention is not limited thereto. Any person familiar with the technology can understand and think of any changes or substitutions within the technical scope disclosed by the present invention, which should be included in the 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 RIS-assisted cognitive radio secure communication transmission method using partial CSI, characterized in that: The following steps are involved: S1. Construct a RIS-assisted cognitive radio wireless secure communication transmission system applicable to partially known CSI; the system includes a main transmitter, a main user with M antennas, a secondary transmitter with D antennas, a secondary user with N antennas, an eavesdropper with E antennas, and a RIS integrating L low-power reflection units; S2. In the RIS-assisted massive MIMO cognitive radio wireless security communication system, in order to enable the secondary transmitter and the secondary user to communicate with the primary transmitter and the primary user in the same frequency band and ensure that the interference of the secondary transmitter to the primary user is within a certain threshold, the initial value of the RIS reflection coefficient matrix is ​​set; S3. Designing a beamforming matrix using part of the CSI. Designing a beamforming matrix using part of the CSI includes the following steps: Beamforming Matrix Q * for: Among them, K and Λ Q is an auxiliary variable, and its expression is as follows: Among them, max{a,b} means taking the larger number between a and b. is the Taylor expansion center, R a , R P , R b , R e , T a , T P , T b , T e , are deterministic non-negative matrices of dimensions L×L, D×D, N×N, E×E, M×M, L×L, L×L, L×L, L×M, N×L, E×L, and D×L, respectively. The beamforming matrix Q = E{ss H }, () H represents the conjugate transpose of the matrix; the RIS reflection coefficient matrix Φ is a L×L diagonal matrix and Φ=diag([θ1,θ2,...θl...,θ L ] T ), θl is the reflection coefficient and j is the imaginary unit, Indicates the adjustment angle of RIS to the signal and V K and Λ K All through Perform eigenvalue decomposition The obtained auxiliary variable, F b and F e is an auxiliary variable, and its specific expression is as follows: ν is the Q * Meet trQ * ≤MP T The parameter, P T is the total transmitted power, λ is the * Satisfy the interference power constraint E{tr(H P ΦH a Q * (H P ΦH a ) H )}≤MP I , E{·} represents the expectation of the matrix, and the specific expression is: P I is the maximum interference power threshold at the primary user; I M is the M×M identity matrix, It is an equivalent channel parameter based on the system partial CSI, and its specific expression is as follows: Among them, F i , Θ i ,Ξ b ,Ξ e ,Ψ i , Π i , Γ i They are all auxiliary variables and i∈{b,e}. The specific expressions are as follows: Θ i =I L +i1Ψ i R a X b =s 2 I N +b2R b X e =s 2 I E +e2R e In the formula, is the and is the and i1 is b1 and e1 in the above expression; σ 2 is the variance of Gaussian white noise with mean 0, I N is the N×N identity matrix, I E is the E×E identity matrix, and the optimal beamforming matrix Q is obtained opt =Q * ; S4. According to the beamforming matrix, using part of the CSI, designing the RIS reflection coefficient matrix; according to the beamforming matrix, using part of the CSI, designing the RIS reflection coefficient matrix, specifically comprising the following steps: S401, taking the projection gradient parameter μ=0.5, calculating the Lagrangian function of the rate with respect to the interference power constraint The specific expression is as follows: In the formula, Indicates the system safety rate, as follows: Where A is the Lagrange multiplier; S402, update the projection gradient parameter μ * : Where Δ is the step size, Δ=0.1; S403, Order Calculate the phase parameter θ of the RIS reflection coefficient matrix * ,in yes About θ l The derivative of , for any l=1,2,...,L, is: Among them, E ll is a matrix in which all values ​​are 0 except the value of the lth row and lth column, b and e It is an auxiliary function, and its specific expression is as follows: S404, RIS reflection coefficient matrix Φ * =diag(θ * ), and obtain the optimal RIS reflection coefficient matrix Φ opt =Φ * ; S5. Repeat steps S3 and S4 until the system safety rate converges.

2. The RIS-assisted cognitive radio secure communication transmission method using partial CSI according to claim 1, characterized in that: In step S1, the channels H from the secondary transmitter to RIS, RIS to the primary user, RIS to the secondary user, and RIS to the eavesdropper are t They are: in, represents the deterministic line-of-sight component of the channel, represents the non-line-of-sight component of the channel and R t represents the spatial correlation matrix of the receiving antenna, T t represents the spatial correlation matrix of the transmitting antenna, and R a , R P , R b , R e , T a , T P , T b , T e , are deterministic non-negative matrices of dimensions L×L, D×D, N×N, E×E, M×M, L×L, L×L, L×L, L×M, N×L, E×L, and D×L, respectively, representing part of the CSI including large-scale fading and Ricean factors; X t is composed of the random components of the channel, and X a , X P , X b , X e They are L×M, N×L, E×L, and D×L matrices respectively; the transmitted signal s is an M×1 column vector, and the beamforming matrix Q=E{ss H },(·) H represents the conjugate transpose of the matrix; the RIS reflection coefficient matrix Φ is a L×L diagonal matrix and Φ=diag([θ1,θ2,...θl...,θ L ] T ), θl is the reflection coefficient and j is the imaginary unit, Indicates the adjustment angle of RIS to the signal and 3. The RIS-assisted cognitive radio secure communication transmission method using partial CSI according to claim 2, characterized in that: In step S2, an initial RIS reflection coefficient matrix Φ=I is given. L , where I L is the L×L identity matrix.

4. The RIS-assisted cognitive radio secure communication transmission method using partial CSI according to claim 3, characterized in that: In step S5, steps S3 and S4 are repeated until the system safety rate is Converge to obtain the optimal system safety rate.

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