Secrecy sum-rate analysis of massive MIMO systems under dual-threat attacks using normalization methods

• Main Authors: Kishan Neupane, Rami J. Haddad
• Format: Article
• Language: English
• Published: KeAi Communications Co., Ltd. 2019-11-01
• Series: Digital Communications and Networks
• Online Access: http://www.sciencedirect.com/science/article/pii/S235286481830049X

Massive Multiple Input Multiple Output (MIMO) has been considered as an emerging technology to enhance the spectral and energy efficiency for the upcoming wireless communication systems. This paper derives a closed-form approximation for the Ergodic Achievable Secrecy Sum-Rate (EASSR) by considering the joint impact of eavesdroppers and jammers. Two widely used linear precoding techniques, Zero-Forcing (ZF) and Maximum Ratio Transmission (MRT), were used in conjunction with matrix and vector normalization to analyze the secrecy performance. Closed-form expressions are used to explain how the secrecy performance is affected when using the ZF and MRT precoding in the eavesdropping and jamming attack models. We also analyze and compare the performances of different combinations of normalization method and precoding technique in various scenarios. From the analytical expressions and simulation results, we observe that the vector and matrix normalization perform better for the ZF precoding than for the MRT precoding in high Signal-to-Noise Ratio (SNR) scenarios. However, in low SNR, the MRT with matrix normalization outperforms the ZF with vector normalization regardless of the number of users in the system. Further, we observe that the MRT fails to serve more than two users in high SNR scenario. Numerical results obtained from Monte Carlo simulation are used to corroborate the accuracy of the asymptotic secrecy analysis. Keywords: Massive MIMO, Linear precoding, Normalization methods, Secrecy analysis