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A Coordinated Approach to Channel Estimation in Large-Scale Multiple-Antenna Systems

机译:大规模多天线系统中信道估计的协调方法

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This paper addresses the problem of channel estimation in multi-cell interference-limited cellular networks. We consider systems employing multiple antennas and are interested in both the finite and large-scale antenna number regimes (so-called "massive MIMO"). Such systems deal with the multi-cell interference by way of per-cell beamforming applied at each base station. Channel estimation in such networks, which is known to be hampered by the pilot contamination effect, constitutes a major bottleneck for overall performance. We present a novel approach which tackles this problem by enabling a low-rate coordination between cells during the channel estimation phase itself. The coordination makes use of the additional second-order statistical information about the user channels, which are shown to offer a powerful way of discriminating across interfering users with even strongly correlated pilot sequences. Importantly, we demonstrate analytically that in the large-number-of-antennas regime, the pilot contamination effect is made to vanish completely under certain conditions on the channel covariance. Gains over the conventional channel estimation framework are confirmed by our simulations for even small antenna array sizes.
机译:本文解决了多小区干扰受限的蜂窝网络中的信道估计问题。我们考虑使用多个天线的系统,并且对有限和大规模天线数量体制(所谓的“大规模MIMO”)都感兴趣。这样的系统通过在每个基站处应用的每小区波束成形来处理多小区干扰。这种网络中的信道估计(已知会受到导频污染效应的阻碍)构成了总体性能的主要瓶颈。我们提出了一种新颖的方法,通过在信道估计阶段本身中实现小区间的低速率协调来解决此问题。协调利用了有关用户信道的附加二阶统计信息,这些信息被显示为区分甚至强相关导频序列的干扰用户提供了一种有力的方法。重要的是,我们通过分析证明,在大量天线的情况下,使导频污染效应在某些条件下完全消除了信道协方差。即使对于较小的天线阵列尺寸,我们的仿真也证实了传统信道估计框架的收益。

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