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Pilot decontamination under imperfect power control

机译:在不完全功率控制下的试验净化

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In a time-division duplex (TDD) multiple antenna system the channel state information (CSI) can be estimated using reverse training. In multicell multiuser massive MIMO systems, pilot contamination degrades CSI estimation performance and adversely affects massive MIMO system performance. In this paper we consider a subspace-based semi-blind approach where we have training data as well as information bearing data from various users (both in-cell and neighboring cells) at the base station (BS). Existing subspace approaches assume that the interfering users from neighboring cells are always at distinctly lower power levels at the BS compared to the in-cell users. In this paper we do not make any such assumption. Unlike existing approaches, the BS estimates the channels of all users: in-cell and significant neighboring cell users, i.e., ones with comparable power levels at the BS. We exploit both subspace method using correlation as well as blind source separation using higher-order statistics. The proposed approach is illustrated via simulation examples.
机译:在时分双工(TDD)中,可以使用反向训练估计信道状态信息(CSI)。在Multicell Multimer Matherive MIMO系统中,导频污染降低CSI估计性能,并对大规模的MIMO系统性能产生不利影响。在本文中,我们考虑了一种基于子空间的半盲方法,在那里我们在基站(BS)上有培训数据以及来自各种用户(互相邻接单元)的信息的信息。现有子空间方法假设来自相邻小区的干扰用户始终处于与内部用户的用户相比在BS的明显较低的功率电平。在本文中,我们没有任何这种假设。与现有方法不同,BS估计所有用户的频道:单元内和重要的相邻小区用户,即BS的具有可比功率电平的相邻小区用户。我们使用高阶统计使用相关性以及盲源分离来利用子空间方法。所提出的方法是通过仿真示例进行说明的。

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