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Title: Mitigating Smart Jammers in MU-MIMO via Joint Channel Estimation and Data Detection
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 simulation results show that MAED effectively mitigates a wide range of smart jamming attacks without having any a priori knowledge about the attack type.  more » « less
Award ID(s):
1717559
NSF-PAR ID:
10434365
Author(s) / Creator(s):
;
Date Published:
Journal Name:
IEEE International Conference on Communications
Page Range / eLocation ID:
1336 to 1342
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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