Pilot Contamination Attack Detection for Multi-Cell MU-Massive MIMO System

This work presents a low-complexity pilot contamination attack (PCA) detector for a multi-cell multi-user massive multiple-input, multiple-output (MU-MaMIMO) system. An active eavesdropper (Eve) in the reference cell transmits synchronized training sequence of the legitimate user (LU) under attack in order to alter precoder to steel information in the downlink data phase. The detection of an active Eve is vital for the information security and enhances secrecy capacity of the LU. We formulate binary hypotheses for active Eve detection from the contaminated channel estimation. We provide performance analysis of the proposed detector. The comparison of analysis and Monte Carlo runs verifies the accuracy of the analysis. The simulation results demonstrate that the performance of the proposed PCA detector is better than the well-known minimum descriptive length (MDL) method in low SNR regime.