Research On Precoding Technology For Full-duplex Physical Layer Security

In recent years,in order to achieve safer information transmission and higher spectrum resource utilization,pre-coding techniques for full-duplex(FD)physical layer security have been proposed and studied.Full-duplex communication technology can realize transmit and recept information at the same time.The precoding technology based on physical layer security mainly uses the characteristics of wireless channel to realize the security of communication system.Therefore,the security of system is closely related to the channel state information(CSI).In the actual communication system,many reasons will cause imperfect CSI.In the case of imperfect CSI,nonrobust precoding scheme is difficult to satisfy the security of the system,so it is very important to study the robust precoding scheme under imperfect CSI.In this thesis,a full-duplex bi-directional secure transmission model is proposed to optimize the structure of the transceiver by using the secret transmission as a criterion to explore the physical layer security performance limit in bidirectional full duplex transmission mode.The specific research contents are as follows:Firstly,for the perfect CSI,aiming at the problem of high complexity of traditional precoding scheme,two low complexity precoding schemes are proposed in this thesis.One is to obtain the semi-closed solution according to the dual problem(DP)of the convex subproblem,then prove the convergence of the algorithm.The other is to use the zero-forcing(ZF)algorithm to eliminate the self-interference and then obtain the suboptimal precoding scheme.Simulation results show that the performance of the two full-duplex precoding schemes is far superior to the half-duplex precoding scheme.Secondly,for the bound CSI error model,a robust precoding scheme with CSI error is designed.Since the optimization problem of robust confidential transmission capacity is non-convex and difficult to solve,two robust precoding schemes are proposed in this thesis.When the eavesdropping channel error is a determined and bounded CSI error model,and the eavesdropping channel covariance error is a determined and bounded CSI error model,this thesis transform the constraint with channel error and use the Difference-of-Convex(DC)programming to convert the nonconvex optimization problem into a series of convex optimization problems.The simulation results show that the two robust precoding algorithms satisfy the convergence.When the CSI is imperfect,the robust precoding scheme is superior to the non-robust precoding scheme.Finally,for the stochastic CSI error model,a robust coding scheme with random error is designed.The existing random error model usually assumes a well-known error distribution function,but in physical layer security applications,this assumption is difficult to satisfy.This thesis considers a statistical CSI error model based on the second moment.The model depends only on the mean and covariance of the error,and does not need to know the complete error distribution function,so it is robust to the error distribution function.For the statistical CSI error model,three robust precoding schemes are proposed in this thesis.When only kown the mean and covariance of the eavesdropping channel error and the exact distribution is not available,the scheme one uses the Markov inequality to approximate the probability constraint condition;the scheme two converts the probability constraint condition equivalently.When only kown the estimated first and second-order moment information on Eve's CSI and the exact distribution is not available,the probability constraint is conservatively estimated.The simulation results show that the three algorithms are convergent and robust.