Physical Layer Security Wireless Commuincation Via Intelligent Reflting Surface

With the rapid development of wireless communication,the importance of information security is rising.Due to the broadcast of wireless communication,the signal transmitted by traditional encryption technology is likely to be obtained by eavesdroppers and cracked by high-performance computer,while the physical layer security technology applies to the bottom side of the communication protocol,which takes advantage of the features and principles of wireless system to achieve secure communication,increasing the difficulty for eavesdroppers to obtain information and anti-attack performance.On the other hand,the Intelligent Reflecting Surface(IRS)composed of large-scale low-cost passive reflective elements can reflect and change the base station beam as required,and has huge application prospects in the field of physical layer security.This paper considers the physical layer security of wireless communication in scenarios involving a base station,an IRS,a legitimate user,and multiple eavesdroppers.The specific research work of this paper is as follows:This paper aims to maximize the security rate of legitimate users under the dual constraints of the total power of the base station and limited resolution of the IRS reflection unit,and the base station precoding vector,artificial noise vector and IRS reflection coefficient are optimized.Considering that the base station precoding vector,artificial noise vector and IRS reflection coefficient are coupled with each other,which is difficult to solve directly.This paper presents a design method based on alternate optimization,which includes two stages in each iteration of the solution.In the first stage,given the IRS reflection coefficient,the base station precoding vector and artificial noise vector are designed.For this non-convex optimization problem,the method of constructing function,semi-definite relaxation and minimax theorem is used to convert this problem into a convex optimization problem.In the second stage,given the base station precoding vector and artificial noise vector,the IRS reflection coefficient is designed.For this discrete optimization problem,this paper proposes a genetic algorithm-based IRS reflection coefficient design method by updating the discrete distribution probability of the optimal IRS phase.Run the above two stages iteratively until the difference between the objective functions of two adjacent iterations is less than a certain threshold.The simulation results show that,compared with the existing methods,the optimized design method given in this paper can achieve a higher security rate,especially when the resolution of the IRS reflection unit is low.This paper also aims to maximize the energy efficiency of the base station,and optimizes the design of base station precoding vector,artificial noise vector and IRS reflection coefficient under the requirement of security rate threshold for legal user.In order to solve the fractional programming problem,this paper uses the Dinkelbach method to transform the original problem,and further decomposes it into two-stage iterative problem through an alternate optimization scheme.In the first stage,the IRS reflection coefficient is fixed,and the base station precoding vector and artificial noise vector are designed.Due to the restriction of the legal user security rate threshold,the optimization problem is non-convex and difficult to solve directly.This paper uses Successive Convex Approximation to design the base station precoding vector and artificial noise vector.In the second stage,the base station precoding vector and artificial noise vector are fixed,and the IRS reflection coefficient is designed.In this paper,an IRS reflection coefficient design algorithm based on gradient search is given by calculating the gradient of the phase angle of each reflection unit.Run the above two stages iteratively until the difference between the objective functions of two adjacent iterations is less than a certain threshold.The simulation results show that the optimized design algorithm proposed in this paper can achieve higher energy efficiency compared with the existing algorithm,especially in scenarios where the security rate threshold is lower.