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