阅读说明：本技术 提升基于智能反射表面的无线通信系统安全速率的方法 (Method for improving safety rate of wireless communication system based on intelligent reflection surface ) 是由 李云 刘炼 彭德义 曾凯洛 于 2021-10-21 设计创作，主要内容包括：本发明属于移动通信技术领域,涉及一种提升基于智能反射表面的无线通信系统安全速率的方法；所述方法包括在智能反射表面的多输入单输出传输系统中,建立出不受信任节点的安全速率最大化模型；固定智能反射表面的角度变量,计算得到波束赋形向量的最优解；固定波束赋形向量,并结合分式编程引入松弛变量对目标函数化简；固定智能反射表面的反射单元的角度变量,求解出松弛变量的优化解；将松弛变量结合增广拉格朗日法引入复制变量更新目标函数；通过交替方向乘子法和连续凸逼近方法计算得到智能反射表面的角度的最优解；将两个最优解带入安全速率最大化模型中,计算得到系统的安全速率值。本发明能够大幅度降低算法复杂度,并提升安全速率。(The invention belongs to the technical field of mobile communication, and relates to a method for improving the safety rate of a wireless communication system based on an intelligent reflecting surface; the method comprises the steps of establishing a security rate maximization model of an untrusted node in a multi-input single-output transmission system of an intelligent reflection surface; fixing the angle variable of the intelligent reflecting surface, and calculating to obtain the optimal solution of the beam forming vector; fixing a beam forming vector, and introducing a relaxation variable to simplify a target function by combining fractional programming; fixing the angle variable of the reflection unit of the intelligent reflection surface, and solving an optimized solution of a relaxation variable; introducing a relaxation variable into a replication variable to update a target function by combining an augmented Lagrange method; calculating to obtain an optimal solution of the angle of the intelligent reflecting surface by an alternating direction multiplier method and a continuous convex approximation method; and (4) bringing the two optimal solutions into a safety rate maximization model, and calculating to obtain a safety rate value of the system. The invention can greatly reduce the algorithm complexity and improve the safety rate.)

1. A method for increasing the security rate of a wireless communication system based on a smart reflective surface, the method comprising:

s1, establishing a multi-input single-output transmission system based on the intelligent reflection surface, wherein the transmission system comprises the intelligent reflection surface, a legal information sender, a legal information receiver and an untrusted node;

s2, establishing a safety rate maximization model according to the lowest energy collection constraint of the untrusted node, the highest energy constraint of a legal information sender and the discrete phase value constraint of the intelligent reflection surface;

s3, fixing the angle variable of the intelligent reflection surface, updating the safe speed maximization model, and calculating to obtain the optimal solution of the beam forming vector;

s4, fixing a beamforming vector, updating the safe speed maximization model, and simplifying an objective function of the updated safe speed maximization model by introducing a relaxation variable in combination with fractional programming;

s5, in the simplified safety speed maximization model, fixing the angle variable of the reflection unit of the intelligent reflection surface, and solving an optimized solution of a relaxation variable;

s6, bringing the optimized solution of the relaxation variables into a simplified security rate maximization model, and introducing a replication variable to update an objective function of the security rate maximization model by combining with an augmented Lagrange method;

s7, in the safety speed maximization model for updating the objective function, calculating to obtain the optimal solution of the angle of the intelligent reflection surface by an alternating direction multiplier method and a continuous convex approximation method;

and S8, bringing the optimal solution of the beamforming vector and the optimal solution of the angle of the intelligent reflection surface into a safe speed maximization model, and calculating to obtain a safe speed value of the system.

2. The method of claim 1, wherein the safe rate maximization model in step S2 comprises:

s.t.C₁:P_E≥e_min

C₂:||ω||²≤P_max

C₃:θ_n∈κ

wherein the content of the first and second substances,an objective function representing a safe rate maximization model; theta represents the angle variable of the intelligent reflecting surface, and omega is the linear beam forming vector at the position of the legal information sender; r_secIndicating a secure rate, R, from a legitimate sender of information to a legitimate receiver of information_sec＝[R_LR-R_E]⁺，R_LRIndicating the receiving rate of the legitimate information receiver,R_Eindicating the reception rate of the untrusted node,[]⁺indicating taking a larger value compared to 0;representing a channel vector from a legitimate information recipient to the intelligent reflective surface; g denotes the legitimate sender of the information to the Intelligent inverseA channel vector of the launch surface;a channel vector representing a legitimate information sender to a legitimate information receiver;representing a channel vector from the intelligent reflecting surface to the untrusted node;a channel vector representing a legitimate information sender to an untrusted node;representing a legitimate information recipient noise power;representing an untrusted node noise power; w represents a beamforming vector, and W ═ ω^HThe upper right superscript H denotes the hermitian matrix; theta represents a diagonal matrix of the intelligent reflecting surface, namely a phase shift matrix; constraint C₁Is the minimum energy harvesting requirement of the untrusted node, P_ERepresenting the collected energy at the untrusted node,constraint C₂Is the highest energy limit, P, of legitimate senders of information_maxRepresents the maximum transmission energy at the legitimate sender of the information; constraint C₃Is the discrete phase value limit of the intelligent reflecting surface; theta_nRepresents an angle variation of the nth reflection unit,κ represents a set of discrete phase values for the smart reflective surface.

3. A lift according to claim 2The method for the safe speed of the wireless communication system based on the intelligent reflecting surface is characterized in that in the step S3, the angle variable of the intelligent reflecting surface is fixed, the safe speed maximization model is updated, the optimal solution of the beam forming vector obtained by calculation is included under the diagonal matrix of the given intelligent reflecting surface, and h is enabled to be_R＝G^HΘ^Hh_IRAnd h_E＝G^HΘ^Hh_IEUpdating the safe rate maximization model, and calculating to obtain an optimal solution W of a beamforming vector, wherein the updated safe rate maximization model is represented as:

s.t.

wherein h is_RA composite channel vector representing a legitimate information recipient,a composite channel vector representing a legitimate information recipient; h is_EA composite channel vector representing untrusted nodes,a composite channel vector representing untrusted nodes; w ° ═ P_maxgg^H(ii) a g is a matrixI represents an identity matrix; constrainingIs the minimum energy harvesting requirement of the untrusted node, P_ERepresenting the collected energy at the untrusted node; constrainingIs the highest energy limit of the legitimate sender of information; tr () represents the trace of the matrix.

4. The method for increasing the security rate of a wireless communication system based on intelligent reflective surfaces as claimed in claim 2, wherein in step S4:

the updated safe rate maximization model is represented as:

s.t.C₁,C₃,

the objective function of the above-mentioned safe rate maximization model is simplified as follows:

s.t.C₁,C₃

introducing relaxation variable epsilon ═ epsilon₁,ε₂]^TAnd further converting into the following steps through fractional programming and mathematical conversion:

s.t.C₁,C₃

wherein f (θ) represents a zeroth function of an angle variable with respect to the intelligent reflecting surface; f (θ, ε) represents a function of the angular and relaxation variables for the intelligent reflective surface; f. of₁(theta) represents a first function of an angular variation with respect to the intelligent reflective surface,f₂(theta) represents a second function of the angular variation with respect to the intelligent reflective surface, and isθ＝[θ₁,θ₂,...,θ_N]^H＝[q₁,q₂,…,q_N]^H，The upper right hand notation represents the conjugate of the matrix; epsilon₁Representing a first slack variable; epsilon₂Representing a second slack variable.

5. The method of claim 4, wherein the step of solving the optimized solution of the slack variable in step S5 comprises obtaining an optimal value of the slack variable ε ° by a derivation operation given a set of angle values of the initial intelligent reflective surfaces, and recording the optimal value as the valueWhereinRepresenting the first slack variable optimization solution, representing the second slack variable optimization solution,

6. the method according to claim 5, wherein the step S6 of introducing a copy variable in combination with the augmented Lagrangian method to update the objective function of the security rate maximization model comprises:

s.t.C₁,C₃

wherein the content of the first and second substances,representing a function of an angle variable, a replication variable, and an augmented lagrange multiplier variable with respect to the intelligent reflective surface; l represents a replication variable; λ represents an augmented lagrange multiplier variable; a ═ epsilon₁ ²+ε₂ ²)cc^H，B＝ε₁ ^*a-(ε₁ ²+ε₂ ²)d^*c，I_F(. cndot.) is an illustrative function, i.e. if θ_n∈κ，I_F(θ_n) 0, otherwise, then I_F(θ_n) Infinity, +,; ρ represents the augmented lagrange multiplier.

7. The method as claimed in claim 6, wherein the step S7 of calculating the optimal solution of the angle of the intelligent reflection surface by the alternating direction multiplier method and the successive convex approximation method comprises:

during the (k + 1) th iteration, the condition of theta is updated for the fixed parameters l, lambdaUnder the condition of constraint C₁Preprocessing, and expanding and scaling the constraint C by a second-order Taylor inequality₁Is converted intoWhereinTaking a set of initial angle values theta₀Obtaining an optimal value of the angle by a continuous convex approximation method; and finding out a target value theta in the (k + 1) th iteration process from the discrete values according to the projection theorem^k+1(ii) a Fixing the parameters lambda and theta, updating l, and obtaining the optimal solution of the parameter l in the (k + 1) th iteration process through a matrix derivation rule

Fixing the parameters l and theta, updating the lambda, and obtaining the optimal solution of the parameter lambda in the k +1 iteration process through an iteration expression of an alternative optimization method

Updating the three parameters until l^k+1-θ^k+1If | | is less than or equal to xi, the iteration process is stopped.

Where ξ represents the set convergence accuracy; the superscript k denotes the kth iteration, and the superscript k +1 denotes the kth +1 iteration.

8. The method as claimed in claim 7, wherein the step of obtaining the safe speed value of the system in step S8 comprises obtaining the optimal angle valueConverting the data into a corresponding theta value, and calculating the safe speed value of the system by combining the optimal solution W DEG of the beamforming vector obtained in the step S3 to obtain the safe speed value of the systemUntil the safe rate converges.

Technical Field

The invention belongs to the technical field of mobile communication, and relates to a method for improving the safety rate of a wireless communication system based on an intelligent reflection surface.

Background

An Intelligent Reflecting Surface (IRS) is one of the key technologies of the next-generation mobile communication system. Recent research on IRS, which can effectively improve the spectral efficiency and energy efficiency of wireless communication, has been a hot spot. The IRS is formed from a plurality of low energy passive super-surface reflecting elements, and each reflecting element is capable of reflecting a signal independently by adjusting the phase of the IRS controller. By adjusting the phases of all the reflection units simultaneously, the IRS can control the magnitude and direction of the reflected electromagnetic wave signals, so that the signals received at the terminal are enhanced.

IRS has been widely used in various wireless communication models to improve the performance index of communication. For example: the IRS is applied to improving the energy efficiency and the spectrum efficiency of a communication system, the IRS is applied to enhancing the communication between the unmanned aerial vehicle and a ground user, and the IRS can also be applied to an energy-carrying communication network.

With the widespread application of IRS, the issue of IRS enhanced security of the wireless communication physical layer has attracted a lot of attention. In a communication system with multiple-input single-output (MISO) existing for an eavesdropper, the existing algorithm comprises an alternating iterative optimization algorithm with fixed variables, the algorithm optimizes one parameter and the other parameter by fixing the other parameter to solve the system security rate, firstly, a phase shift matrix of an IRS is fixed to obtain an optimal beamforming vector solution, then, the beamforming vector is fixed, then, semi-positive definite relaxation and Charnes-Cooper transformation are combined to carry out scaling on the IRS phase shift matrix constraint, and finally, an optimal solution meeting the constraint requirement is obtained by a discrete randomization method, but the algorithm based on the semi-positive definite relaxation scaling has higher complexity. Another commonly used algorithm is a matrix inequality scaling algorithm based on fractional programming, which obtains an optimal closed-form solution of transmit beamforming and a semi-closed-form solution of the IRS phase shift matrix through a scaling mathematical technique, and generally considers that a phase is a continuous value. Another alternative method introduces an interference signal similar to artificial noise at the transmitting end, and suppresses the rate of the eavesdropper by combining the interference signal into the transmit beamforming and then combining an alternative optimization algorithm, which needs to introduce an additional transmitting unit. At present, most of researches adopt the condition that IRS phase values are continuous or adopt a common alternative optimization algorithm, but the processing complexity is higher.

Disclosure of Invention

Based on the problems in the prior art, considering that the discrete phase in practical application better meets the practical cost requirement, the reduction of the complexity of the algorithm becomes a key, so that the research of the discrete phase-based low-complexity algorithm in the IRS-MISO system has important value and significance. The invention aims to provide a method for enhancing the safety rate of a wireless communication system by using an intelligent reflecting surface.

In order to achieve the above object, the present invention provides a method for increasing the security rate of a wireless communication system based on an intelligent reflective surface, the method comprising:

s1, establishing a multi-input single-output transmission system based on the intelligent reflection surface, wherein the transmission system comprises the intelligent reflection surface, a legal information sender, a legal information receiver and an untrusted node;

s2, establishing a safety rate maximization model according to the lowest energy collection constraint of the untrusted node, the highest energy constraint of a legal information sender and the discrete phase value constraint of the intelligent reflection surface;

s3, fixing the angle variable of the intelligent reflection surface, updating the safe speed maximization model, and calculating to obtain the optimal solution of the beam forming vector;

s4, fixing a beamforming vector, updating the safe speed maximization model, and simplifying an objective function of the updated safe speed maximization model by introducing a relaxation variable in combination with fractional programming;

s5, in the simplified safety speed maximization model, fixing the angle variable of the reflection unit of the intelligent reflection surface, and solving an optimized solution of a relaxation variable;

s6, bringing the optimized solution of the relaxation variables into a simplified security rate maximization model, and introducing a replication variable to update an objective function of the security rate maximization model by combining with an augmented Lagrange method;

s7, in the safety speed maximization model for updating the objective function, calculating to obtain the optimal solution of the angle of the intelligent reflection surface by an alternative multiplier optimization method and a continuous convex approximation method;

and S8, bringing the optimal solution of the beamforming vector and the optimal solution of the angle of the intelligent reflection surface into a safe speed maximization model, and calculating to obtain a safe speed value of the system.

The invention has the beneficial effects that:

aiming at the problem of the security rate of an untrusted eavesdropper node in a wireless communication network, the invention firstly constructs a security rate maximization model in an IRS-MISO system, converts the non-convex problem into the convex optimization problem by a fractional programming and alternative optimization method, and respectively updates three variables by combining an alternative direction multiplier method, thereby greatly reducing the algorithm complexity. Simulation results show that compared with the situation that the IRS is not adopted and the IRS phase value is random, the safety rate of the system is greatly improved.

Drawings

FIG. 1 is a flow chart of an IRS for enhancing the safe transmission rate algorithm of a wireless communication network according to the present invention;

FIG. 2 is a diagram of an IRS-MISO system model employed in the present invention;

FIG. 3 is a diagram of simulated position coordinates for an IRS-MISO system employed in the present invention;

FIG. 4 is a comparative simulation diagram of system security rates under different minimum energy requirements of untrusted nodes in accordance with the present invention;

FIG. 5 is a simulation chart of the system safety rate comparison under different maximum transmission powers according to the present invention;

FIG. 6 is a simulation chart of the system safety rate comparison for different IRS reflection unit numbers according to the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Fig. 1 is a flowchart of an algorithm for enhancing the secure transmission rate of the wireless communication network by the IRS according to the present invention, and as shown in fig. 1, the method includes:

s1, establishing a multi-input single-output transmission system based on the intelligent reflection surface, wherein the transmission system comprises the intelligent reflection surface, a legal information sender, a legal information receiver and an untrusted node;

in the embodiment of the present invention, it is assumed that an IRS-MISO system is composed of a legal information sender (LT) and a legal information receiver (LR) as well as an Intelligent Reflection Surface (IRS) and an UN (untrusted node), the model diagram of the system is shown in fig. 2, LT and IRS communicate through a channel G, LT and UN communicate through a channel GCommunication, IRS and UN through channelsCommunication, IRS and LR over a channelAnd (4) communication.

S2, establishing a safety rate maximization model according to the lowest energy collection constraint of the untrusted node, the highest energy constraint of a legal information sender and the discrete phase value constraint of the intelligent reflection surface;

in the embodiment of the present invention, the channel matrix G is initialized,and a beam forming vector omega, initializing a phase shift matrix theta of the IRS, and respectively representing received signals at a legal information receiver and an untrusted node asAndobtaining the receiving rates of a legal information receiver and an untrusted node respectively according to the Shannon formulaAndobtaining an objective function R of the system_sec＝[R_LR-R_E]⁺，[]⁺Indicating a larger value compared to 0.

Wherein the content of the first and second substances,is a linear beamforming vector at LT, and the transmission signal s satisfies E { s²}＝1，The channels are respectively corresponding to the links LT-IRS, LT-LR, IRS-LR, LT-UN and IRS-UN. Θ ═ diag (q) is the diagonal matrix of IRS, q ═ q (q)₁,q₂,…q_N)，θ_nIs the phase shift (angle) of the nth reflection unit, m discrete phase values are obtained by uniformly quantizing r bits, κ represents a set of discrete phase values for the smart reflective surface. n is_LRAnd n_EObey a mean of 0 and a variance of σ at the legitimate information recipient and the untrusted node, respectively²Gaussian noise.

Assume the collected energy at UN isMaximum transmission energy at LR is P_maxThe following safe rate maximization model can be obtained:

s.t.C₁:P_E≥e_min

C₂:||ω||²≤P_max

C₃:θ_n∈κ

wherein the content of the first and second substances,an objective function representing a safe rate maximization model; theta represents the angle variation of the intelligent reflecting surface,representing a channel vector from a legitimate information recipient to the intelligent reflective surface; g represents a channel vector from a legal information sender to the intelligent reflecting surface;a channel vector representing a legitimate information sender to a legitimate information receiver;representing a channel vector from the intelligent reflecting surface to the untrusted node;a channel vector representing a legitimate information sender to an untrusted node;representing a legitimate information recipient noise power;representing an untrusted node noise power; w represents a beamforming vector, and W ═ ω^HThe upper right scale H represents a Hermite matrix theta which represents a diagonal matrix of the intelligent reflection surface, namely a phase shift matrix; constraint C₁Is the lowest energy harvesting requirement for untrusted nodes; constraint C₂Is the highest energy limit of the legitimate sender of information; constraint C₃Is a discrete phase value limit of the intelligent reflective surface.

S3, fixing the angle variable of the intelligent reflection surface, updating the safe speed maximization model, and calculating to obtain the optimal solution of the beam forming vector;

in the embodiment of the invention, the phase shift matrix theta of the IRS is fixed through the angle variable of the intelligent reflecting surface, namely the discrete phase value limit constraint of the intelligent reflecting surface is not considered, and h is also set_R＝G^HΘ^Hh_IRAnd h_E＝G^HΘ^Hh_IERewriting the security rate maximization model, expressed as:

wherein h is_RA composite channel vector representing a legitimate information recipient,a composite channel vector representing a legitimate information recipient; h is_EA composite channel vector representing untrusted nodes,representing untrusted nodesThe composite channel vector of (a); constrainingIs the minimum energy harvesting requirement of the untrusted node, P_ERepresenting the collected energy at the untrusted node; constrainingIs the highest energy limit of the legitimate sender of information; tr () represents the trace of the matrix.

By solving the mathematical equation h_R＝G^HΘ^Hh_IR+h_TRAndobtaining the optimal solution of the beam forming vector as W degrees as P_maxgg^H(ii) a g is a matrixI denotes the identity matrix.

S4, fixing a beamforming vector, updating the safe speed maximization model, and simplifying an objective function of the updated safe speed maximization model by introducing a relaxation variable in combination with fractional programming;

in the embodiment of the present invention, a beam forming vector W ° of the IRS is fixed to optimize a phase shift matrix Θ of the IRS, that is, an angle variable Θ of each intelligent reflective surface, and the model can be expressed as:

s.t.C₁,C₃,

using mathematical identitiesθ＝[θ₁,θ₂,...,θ_N]^H＝[q₁,q₂,…,q_N]^HAnd is andsimplifying the objective function, equating the optimized theta to the optimized theta, and simplifying the objective function as follows:

s.t.C₁,C₃

wherein f (θ) represents a zeroth function of an angle variable with respect to the intelligent reflecting surface; f (θ, ε) represents a function of the angular and relaxation variables for the intelligent reflective surface; f. of₁(theta) represents a first function of an angular variation with respect to the intelligent reflective surface,f₂(theta) represents a second function of the angular variation with respect to the intelligent reflective surface,

under the model, the relaxation variable epsilon is continuously introduced to epsilon₁,ε₂]^TThe objective function is further converted into:

s.t.C₁,C₃

wherein epsilon₁Representing a first slack variable; epsilon₂Representing the second relaxation variable, the upper right-hand symbol represents the conjugate of the matrix.

S5, in the simplified safety speed maximization model, fixing the angle variable of the reflection unit of the intelligent reflection surface, and solving an optimized solution of a relaxation variable;

similarly, the optimization solution problem for solving the slack variables described above can still be solved by an alternating optimization method, noting the optimal solution asBy derivationThe optimal solution can be obtained Representing the first slack variable optimization solution,representing a second slack variable optimization solution.

S6, bringing the optimized solution of the relaxation variables into a simplified security rate maximization model, and introducing a replication variable to update an objective function of the security rate maximization model by combining with an augmented Lagrange method;

in the embodiment of the invention, the obtained optimal epsilon DEG value can be brought back to f (theta, epsilon) to be a function only containing a variable theta and expressed asThe optimization problem then transforms to:

s.t.C₁,C₃

introducing a replication variable l, and converting the optimization problem into:

s.t.C₁,C₃

converting the objective function f (l) into an augmented Lagrangian function corresponding to the objective functionExpressed as:

therefore, an objective function of updating the security rate maximization model by introducing the replication variable in combination with the augmented Lagrange method is expressed as follows:

s.t.C₁,C₃

wherein the content of the first and second substances,representing a function of an angle variable, a replication variable, and an augmented lagrange multiplier variable with respect to the intelligent reflective surface; θ represents an angle variable; l represents a replication variable; λ represents an augmented lagrange multiplier variable; a ═ epsilon₁ ²+ε₂ ²)cc^H，B＝ε₁ ^*a-(ε₁ ²+ε₂ ²)d^*c，I_F(. cndot.) is an illustrative function, i.e. if θ_n∈κ，I_F(θ_n) 0, otherwise, then I_F(θ_n) Infinity, +,; ρ represents the augmented lagrange multiplier.

S7, in the safety speed maximization model for updating the objective function, calculating to obtain the optimal solution of the angle of the intelligent reflection surface by an alternating direction multiplier method and a continuous convex approximation method;

in the embodiment of the invention, an Alternating Direction Multiplier Method (ADMM) is adopted to iteratively update the parameters l, theta and lambda;

first, by fixing the parameters l, λ and updating θ, the optimization model can be converted into:

st.C₁

since this is a non-convex problem, it is necessary to introduce a successive convex approximation method, first constraining C₁Performing pretreatment, converting into theta^Hcc^Hθ+2Re{d*θ^Hc}+d²≥e_minLet m (theta) equal to theta^Hcc^Hθ+2Re{d*θ^Hc}+d²The m (theta) is more than or equal to m (theta) by the second-order Taylor expansion scaling₀)+m′(θ₀)(θ-θ₀) The target sub-problem is converted into:

the problem is a convex optimization problem, the problem can be solved by adopting a convex optimization tool CVX, and the obtained result is recorded asThen obtaining the nearest angle value in the angle discrete value set by using the projection theoremNamely the target value theta in the k +1 iteration process^k+1。

In the embodiment of the invention, theta₀Representing an initial angle value given by₀By combining the fixed parameters l, lambda, the calculation can be carried outIteratively solving the target subproblem untilIf epsilon represents the set convergence precision, stopping the iterative solution process of theta and outputting the objective function value in the ith iterative processAnd determines the corresponding theta⁽ⁱ⁾Theta is measured by⁽ⁱ⁾As a target value theta in the (k + 1) th iteration process^k+1I.e. the optimum value. Secondly, fixing the parameters lambda and theta, updating l, and obtaining the optimal solution of the parameter l in the (k + 1) th iteration process as l through a matrix derivation rule^k+1＝(2A+ρΙ_N)^-1(2B+λ^k+ρθ^k+1)；

Thirdly, fixing the parameters l and theta, updating the lambda, and obtaining the optimal solution of the parameter lambda in the current iteration process as lambda through the iteration expression of the alternative optimization method^k+1＝λ^k-ρ(l^k+1-θ^k+1)；

Updating the three parameters until l^k+1-θ^k+1If | | is less than or equal to xi, stopping the iteration process; ξ denotes the set convergence accuracy.

Finally, through the iterative process, the theta in the (k + 1) th iterative process can be obtained^(k+1)The optimum angle value of

And S8, bringing the optimal solution of the beamforming vector and the optimal solution of the angle of the intelligent reflection surface into a safe speed maximization model, and calculating to obtain a safe speed value of the system.

In the embodiment of the present invention, the optimal solution W ° obtained by Θ and the previous step S3 can be calculated to the safe rate R of the system_sec(W, Θ), since steps S3-S7 are an iterative solution process, the security is calculated by iterationThe rate value is up to the rate to convergence accuracy.

By the aid of the method, the safety speed of the system can be rapidly calculated, and the safety speed of the system can be effectively improved.

In some embodiments, in the system model simulation process of the present invention, where IRS-MISO exists in untrusted nodes, the positions of LT, LR, UN, IRS are considered as shown in FIG. 3, where d_LI＝42m，d_v＝3.5m, The number M of antennas of LT is set to 2, and the number N of reflection units of IRS is set to 32. Path loss model l (d) ═ T₀(d/d₀)^-αWherein T is₀Is a reference distance d₀Taking T as road strength loss of 1m₀The distance d is the distance between two nodes, 30 dB. The path loss indexes of LT-LR, LT-IRS, IRS-LR, LT-Eve and IRS-Eve are respectively alpha_TR＝2，α_IR＝2.2，α_LI＝2.2，α_TE＝3，α_IE3. Other parameters are set as:convergence accuracy 10^-6。

By adopting the method for improving the safety rate of the wireless communication system based on the intelligent reflection surface, the following simulation result can be obtained, wherein two simulation reference datum lines are selected for comparison in the embodiment of the invention, Baseline 1 is the system safety rate without using IRS, and Baseline2 is the phase shift random value of the IRS.

FIG. 4 shows the change in the safe rate of the system at different energy harvesting thresholds, setting parameter p_maxAt 20dBm, it can be seen from fig. 4 that as the threshold increases, all the safety rates are in a downward trend, because the value of the energy collection is too high for the total energy, with the total energy being constant.

FIG. 5 shows the effect of different energy transmit powers on the system safety rate at LT, setting the minimum energy requirement e of UN_min3.7 μ w. It can be seen from fig. 5 that the IRS effectively increases the system security rate in all cases, because the IRS can suppress the rate of the untrusted node while increasing the strength of the received signal at the LR, thereby achieving the purpose of increasing the system security rate. In the case of N-32, the algorithm proposed by the present invention improves the performance by 30.1%, and it can be seen from the figure that as the number of reflection units of the IRS increases, the safety rate of the system also increases.

Fig. 6 shows the change of the system safety rate under different IRS reflection unit numbers, and it can be seen from fig. 6 that as the IRS reflection unit number increases, the system safety rate is improved accordingly, because more reflection signals are collected in the reflection unit to reach the receiving end. With respect to baseline2, as the number of bits for quantization of the IRS discrete phase increases, the safe rate of the system increases by 28% and 43% with 1bit and 2 bit.

Aiming at the problem of the security rate of an untrusted eavesdropper node in a wireless communication network, the invention provides an alternative optimization algorithm based on ADMM (adaptive Doppler shift keying) by taking the security rate of an optimization system as an objective function in an IRS-MISO (inter-range interference rejection-single-input single-output) system for the first time, and the complexity is reduced compared with the existing algorithm. Simulation results show that compared with the situation that the IRS is not used and the IRS phase is randomly valued, the safety rate of the system is greatly improved.

In the description of the present invention, it is to be understood that the terms "coaxial", "bottom", "one end", "top", "middle", "other end", "upper", "one side", "top", "inner", "outer", "front", "center", "both ends", and the like, indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention.

Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.