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:现有方法根据对通过专门培训阶段获得的子空间(或接收统计数据)的估计,减轻干扰,这是减少通信率的两个主要缺点:(一) 降低通信率,因为在培训阶段无法传输数据,因此降低了通信率;(二) 可以通过在培训阶段保持安静的智能或多防护干扰器,或者通过时间变化波束来动态地改变其子空间,来回避这一处理这些缺陷的方法。为了解决这些缺陷,我们建议联合减缓干扰器和数据探测,这是减少干扰器的一个新模式。核心想法是,通过在多个时段共同探测数据传输,来估计和消除干扰器干扰子空间。这样就消除了在培训阶段对专门降低费率培训期的需求,同时能够减缓智能和动态的多防护干扰器。我们与SANDMAN(多用户IMIMO上链接JMD的简单而实用算法)一起将我们的范式简单化。广域模拟显示了JMMD的功效,特别是SANMAN的减缓功能。