Multi-antenna (MIMO) processing is a promising solution to the problem of jammer mitigation. Existing methods mitigate the jammer based on an estimate of its subspace (or receive statistics) acquired through a dedicated training phase. This strategy has two main drawbacks: (i) it reduces the communication rate since no data can be transmitted during the training phase and (ii) it can be evaded by smart or multi-antenna jammers that are quiet during the training phase or that dynamically change their subspace through time-varying beamforming. To address these drawbacks, we propose joint jammer mitigation and data detection (JMD), a novel paradigm for MIMO jammer mitigation. The core idea is to estimate and remove the jammer interference subspace jointly with detecting the transmit data over multiple time slots. Doing so removes the need for a dedicated rate-reducing training period while enabling the mitigation of smart and dynamic multi-antenna jammers. We instantiate our paradigm with SANDMAN, a simple and practical algorithm for multi-user MIMO uplink JMD. Extensive simulations demonstrate the efficacy of JMD, and of SANDMAN in particular, for jammer mitigation.

翻译：多天线（MIMO）处理是缓解干扰问题的有效方案。现有方法通过专用训练阶段获取干扰子空间（或接收统计量）的估计值来抑制干扰，但这种策略存在两个主要缺陷：（i）训练阶段无法传输数据，降低了通信速率；（ii）会被在训练阶段保持静默或通过时变波束成形动态改变子空间的智能或多天线干扰机规避。针对这些问题，我们提出联合干扰抑制与数据检测（JMD）这一新颖的MIMO干扰抑制范式。其核心思想是在多时隙检测发射数据的同时，联合估计并消除干扰子空间。这种方法不仅消除了专用训练阶段带来的速率损失，还能有效抑制智能动态多天线干扰机。我们通过SANDMAN算法（一种简单实用的多用户MIMO上行JMD算法）实例化了该范式。大量仿真验证了JMD范式（尤其是SANDMAN算法）在干扰抑制中的有效性。