In this work, we study the secrecy performance of a reconfigurable intelligent surfaces (RIS)-aided wireless communication system in the presence of an eavesdropping user. Specifically, we assume that the RIS is placed between the source and the legitimate user to create a smart environment and used to improve the link security. In particular, analytical results for the secrecy outage probability (SOP) is derived. We also provide an asymptotic analysis to investigate the effect of the main parameters on the secrecy performance of our proposed system, such as the number of the reflectors in the RIS and the average signal-to-noise ratios. Finally, we verify our analytical results via simulations. Results show the positive effect of utilizing the RIS for enhancing wireless systems secrecy performance.

High-speed railway (HSR) wireless communications are required to ensure strict security. In this work, we study the secrecy performance of a nonorthogonal multiple access- (NOMA-) aided HSR wireless communication system in the case of an eavesdropping user. Specifically, applying NOMA technology to the HSR communication system can effectively improve the data rates. Therefore, we study the secrecy performance of the downlink NOMA system under the HSR wireless communication. In particular, the exact analytical results for the secrecy outage probability (SOP) based on no small-scale channel state information (CSI) are derived. We also provide all of the parameterizations for the proposed channel model. Finally, the correctness of theoretical derivation is verified via simulations. Results show the positive effect of utilizing the NOMA for enhancing wireless systems secrecy performance.

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Since the signal with strong power need be demodulated first for successive interference cancellation (SIC) receiver in non-orthogonal multiple access (NOMA) systems, the base station (BS) need inform the near user terminal (UT), which has allocated higher power, of the far UT's modulation mode. To avoid unnecessary signaling overhead of control channel, a blind detection algorithm of NOMA signal modulation mode is designed in this paper. Taking the joint constellation density diagrams of NOMA signal as the detection features, the deep residual network is built for classification, so as to detect the modulation mode of NOMA signal. In view of the fact that the joint constellation diagrams are easily polluted by high intensity noise and lose their real distribution pattern, the wavelet denoising method is adopted to improve the quality of constellations. The simulation results represent that the proposed algorithm can achieve satisfactory detection accuracy in NOMA systems. In addition, the factors affecting the recognition performance are also verified and analyzed.