Title: Joint Jammer Mitigation and Data Detection Show Chinese title

Title: 联合干扰抑制与数据检测

Abstract: Multi-antenna (or MIMO) processing is a promising solution to the problem of jammer mitigation. Existing methods mitigate the jammer based on an estimate of its spatial signature that is 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 do not transmit 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 of JMD is to estimate and remove the jammer interference subspace jointly with detecting the legitimate transmit data over multiple time slots. Doing so removes the need for a dedicated and rate-reducing training period while being able to mitigate smart and dynamic multi-antenna jammers. We provide two JMD-type algorithms, SANDMAN and MAED, that differ in the way they estimate the channels of the legitimate transmitters and achieve different complexity-performance tradeoffs. Extensive simulations demonstrate the efficacy of JMD for jammer mitigation. Show Chinese abstract

Abstract: 多天线（或MIMO）处理是缓解干扰器问题的一种有前景的解决方案。 现有方法基于通过专用训练阶段获得的其空间特征估计来缓解干扰器。 这种策略有两个主要缺点：(i) 它会降低通信速率，因为在训练阶段无法传输数据，(ii) 可能会被智能或多天线干扰器规避，这些干扰器在训练阶段不传输或通过时变波束成形动态改变其子空间。 为解决这些缺点，我们提出了联合干扰器抑制和数据检测（JMD），这是一种新的MIMO干扰器抑制范式。 JMD的核心思想是在多个时间槽上联合估计并消除干扰器干扰子空间，并检测合法发射数据。 这样做消除了专用且速率降低的训练周期的需求，同时能够缓解智能和动态的多天线干扰器。 我们提供了两种类型的JMD算法，SANDMAN和MAED，它们在估计合法发射机信道的方式上有所不同，并实现了不同的复杂度-性能权衡。 大量仿真结果证明了JMD在干扰器抑制方面的有效性。