On Countermeasures of Pilot Spoofing Attack in Massive MIMO Systems: A Double Channel Training Based Approach

摘要

In this paper, we investigate secure communication in a massive multiple-input multiple-output (MIMO) system with multiple users and multiple eavesdroppers (Eve) under both pilot spoofing attack (PSA) and uplink jamming. Specifically, Eve impairs the normal channel estimation by sending identical pilot sequences with the legitimate users. Based on the impaired channel estimation, the base station adopts linear processing schemes for uplink data reception, which is jammed by Eve, and downlink confidential information transmission. We first evaluate the impact of the PSA on the achievable rate with linear processing, and then propose a double channel training based scheme to combat PSA. By using the channel estimation difference in two training phases, the presence of the PSA can be detected and accurate legitimate channel estimation can be obtained by removing the effect of Eve's channel. Furthermore, we analyze the channel estimation errors and derive a closed-form expression of the minimum mean square error precoding scheme to maximize the minimum achievable secrecy rate, which outperforms the conventional linear precoding counterparts.