Blind Channel Separation in Massive MIMO System under Pilot Spoofing and Jamming Attack
This addresses security vulnerabilities in wireless communication for massive MIMO systems, though it appears incremental as it builds on existing channel separation approaches.
The paper tackles the problem of pilot spoofing and jamming attacks in massive MIMO systems by proposing a blind channel separation method that estimates the characteristic function of the desired signal from received pilot signals, achieving good channel separation performance as shown in simulations.
We consider a channel separation approach to counter the pilot attack in a massive MIMO system, where malicious users (MUs) perform pilot spoofing and jamming attack (PSJA) in uplink by sending symbols to the basestation (BS) during the channel estimation (CE) phase of the legitimate users (LUs). More specifically, the PSJA strategies employed by the MUs may include (i) sending the random symbols according to arbitrary stationary or non-stationary distributions that are unknown to the BS; (ii) sending the jamming symbols that are correlative to those of the LUs. We analyze the empirical distribution of the received pilot signals (ED-RPS) at the BS, and prove that its characteristic function (CF) asymptotically approaches to the product of the CFs of the desired signal (DS) and the noise, where the DS is the product of the channel matrix and the signal sequences sent by the LUs/MUs. These observations motivate a novel two-step blind channel separation method, wherein we first estimate the CF of DS from the ED-RPS and then extract the alphabet of the DS to separate the channels. Both analysis and simulation results show that the proposed method achieves good channel separation performance in massive MIMO systems.