智能反射面增强抗干扰与反窃听的安全传输策略

To solve the problem of potential cooperation between eavesdroppers and jammers in wireless communications，a secure transmission strategy with an intelligent reflecting surface （IRS） was proposed to enhance anti-interference and anti-eavesdropping. In this strategy，we account for both perfect and imperfect channel state information（CSI）. We established an IRS-assisted multiple input single output（MISO）secure communication system model. The system’s secrecy rate is maximized by jointly optimizing the base station’s transmit beamforming and the IRS’s phase shift matrix. More specifically，the alternating optimization algorithm and constructor method were presented to solve the secrecy rate optimization problem of a communication system under perfect CSI，where the difference of the convex functions algorithm and first-order Taylor expansion were used to obtain the constraint function under the rank-one constraint，and then the penalty function method was used to bring the penalty term related to the constraint function into the objective function for the solution. To address the non-convex quadratic secrecy rate problem in the communication system，we transformed it into a convex optimization problem. This was achieved using a slack variable，the S-procedure，the Lagrange multiplier method，and alternating optimization，particularly under conditions of imperfect CSI. Furthermore，the base station transmission power，the number of IRS reflection units，channel uncertainty，and other parameters of the system security rate were also analyzed. Numerical results show that the system secrecy rate increases with the increase in the number of IRS reflection units under perfect channel state information and imperfect channel state information. This is because the number of IRS reflection units increases，the diversity gain and degree of freedom in space will increase，and the safety performance of the system will be enhanced. Moreover，the channel uncertainty will result in a channel estimation error，thus leading to a lower secrecy rate for the system in the worst signal transmission environment. Numerical results also show that the proposed strategy can achieve convergence after three to six iterations. The proposed strategy enhances the communication system’s secrecy rate by approximately 20% compared to the existing maximum ratio transmission strategy and the random phase shift strategy.