Research On Physical Layer Security Technology For Millimeter Wave SWIPT IoT Systems

Internet of thing(IoT)technology as one of the key technologies of 5G,in the context of global energy saving and emission reduction,the construction of green IoT communication is an inevitable trend.However,the wired power supply of IoT devices is not suitable for large-scale deployment.Simultaneous wireless information and power transfer(SWIPT),as an emerging technology,can realize the dual utilization of radio frequency(RF)resources,which is a self-sufficient green communication mode.In SWIPT systems,the broadcasting characteristics of radio signals make it possible to transmit information and energy simultaneously,but it also makes the security problem of information eavesdropping unavoidable.The millimeter wave network supporting SWIPT technology can not only make full use of the limited RF resources,but also help energy-constrained mobile devices to effectively solve the problem of excessive power consumption caused by the increase of communication rate.In summary,although there have been many breakthroughs and achievements in recent years regarding millimeter-wave SWIPT technology,there is a lack of research related to physical layer security techniques for channel uncertainty and intelligent reflective surface(IRS)-assisted millimeter-wave SWIPT systems.In this paper,we focus on these difficulties.1)First,millimeter wave IoT secure communication system based SWIPT is investigated.To optimize the secrecy rate of the system.artificial noise(AN)assisted transmission is applied to millimeter wave SWIPT system to prevent energy receivers from eavesdropping on information.A nonlinear energy harvesting model and transmit power constraint are also considered to jointly optimize the digital precoding vector,power splitting(PS)ratio and AN covariance matrix for secure communication,and an alternating optimization algorithm based on semidefinite relaxation(SDR)is proposed to solve the given secrecy rate maximization problem.On the other hand,an alternating optimization algorithm based on zero forcing precoding is proposed to reduce the complexity of the system.Finally,simulation results verify the effectiveness of the proposed algorithm.2)Then,in the case of channel uncertainty in millimeter wave IoT systems with PS SWIPT,a joint digital precoding vector,AN covariance matrix and PS ratio optimization problem is investigated to maximize the secrecy rate of the system.However,due to the existence of non-convexity and coupling variables,the optimization problem is non-convex.In the case of imperfect channel state information(CSI),a joint alternating optimization algorithm is proposed to transform the nonconvex problem into a convex problem by combining the SDR method and SProcedure Lemma.In addition,construct a convex approximation constraint to guarantee rank 1 constraint.Finally,the simulation results show that,compared with the scheme without AN,the secrecy rate has been increased by 63% in the case of perfect CSI and 107% in the case of imperfect CSI.3)Finally,the security of the wireless communication system is enhanced and the secrecy rate of the system is increased by IRS-assisted technology,in which the information receiver is considered SWIPT.When the energy receivers act as potential eavesdroppers,IRS is deployed near the information receiver to assist the secure transmission of information from the base station,jointly optimizing the transmit beamforming,PS ratio,IRS reflective beamforming and AN covariance matrix to maximize the achievable secrecy rate.Due to the existence of nonconvexity of the objective function and the presence of coupling variables,the problem remains nonconvex.Therefore,a joint alternating optimization algorithm based on SCA is proposed to solve the secure transmission problem in the case of imperfect CSI.Finally,the simulation results show that the IRS-assisted technology can effectively enhance the system security.