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Wireless systems must be resilient to jamming attacks. Existing mitigationmethods require knowledge of the jammer's transmit characteristics. However,this knowledge may be difficult to acquire, especially for smart jammers thatattack only specific instants during transmission in order to evade mitigation.We propose a novel method that mitigates attacks by smart jammers on massivemulti-user multiple-input multiple-output (MU-MIMO) basestations (BSs). Ourapproach builds on recent progress in joint channel estimation and datadetection (JED) and exploits the fact that a jammer cannot change its subspacewithin a coherence interval. Our method, called MAED (short for MitigAtion,Estimation, and Detection), uses a novel problem formulation that combinesjammer estimation and mitigation, channel estimation, and data detection,instead of separating these tasks. We solve the problem approximately with anefficient iterative algorithm. Our results show that MAED effectively mitigatesa wide range of smart jamming attacks without having any a priori knowledgeabout the attack type.

Mitigating Smart Jammers in MU-MIMO via Joint Channel Estimation and Data Detection