Impact of Cooperative Attack on User Scheduling in Massive MIMO Systems

In this paper, the downlink user scheduling design of a massive multiple-input multiple-output (MIMO) is investigated in the presence of multiple active attackers. A large-scale antenna array base station (BS) with zero-forcing (ZF) precoders transmits confidential information to multiple scheduled users via random user selection. Meanwhile, multiple active attackers collaboratively contaminate the uplink channel estimates by sending pilot sequences identical to those of the legitimate users, aiming at minimizing the number of scheduled users of the legitimate system. First, we evaluate the impact of this cooperative attack on the uplink channel training results and derive an analytical expression for the achievable downlink sum-rate of ZF precoders aided massive MIMO system. Then, relying on the random matrix theory (RMT)-based large-system analysis, we derive a deterministic approximation of the achievable downlink sum-rate. Furthermore, we formulated an optimization problem from the standpoint of the attackers to minimize the number of the scheduled users. Numerical results verify the correctness of the theoretical analyses, and reveal that cooperative attack has a great impact on the downlink user scheduling design.