Physical Layer Security Enhancement with Large Intelligent Surface-Assisted Networks

Large intelligent surface (LIS)-aided wireless communications have drawn significant attention recently. We study the physical layer security of the downlink LIS-aided transmission framework for randomly located users in the presence of a multiple-antenna eavesdropper. To show the advantages of LIS-aided networks, we consider two practice scenarios: Communication with and without LIS. In both cases, we apply the stochastic geometry theory to derive exact probability density function (PDF) and cumulative distribution function (CDF) of signal-to-interference plus noise ratio. Furthermore, the obtained PDF and CDF are used to evaluate important security performance of wireless communication including the secrecy outage probability, the probability of nonzero secrecy capacity, and the average secrecy rate. In order to validate the accuracy of our analytical results, extensive Monte-Carlo simulations are subsequently conducted which provide interesting insights on how the secrecy performance is influenced by various important network parameters. Our results show that compared with the communication scenario without an LIS, the deployment of LIS can improve the performance and enhance the communication security substantially. In particular, the security performance of the system can be significantly improved by increasing the number of reflecting elements equipped in an LIS.