1 research outputs found
Blind Channel Separation in Massive MIMO System under Pilot Spoofing and Jamming Attack
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