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Antenna selection for massive MIMO Kronecker channel models using non-central principal component analysis

机译:使用非中心主成分分析的大规模MIMO Kronecker信道模型的天线选择

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Massive multi-user multiple-input-multiple-output (MU-MIMO) is an emerging fifth-generation (5G) wireless communication technology. However, the deployment of large numbers of antennas and radio frequency (RF) chains needed at the base stations (BS) in massive MIMO brings challenges of high system complexity and hardware energy consumption. By using Kronecker channel modeling, a simple stochastic MIMO model for a narrowband channel is developed that uses the correlation matrices at the mobile station (MS) and BS. In this paper, two semi-heuristic techniques are proposed for practical antenna selection considering Kronecker channel modeling in a MU-MIMO broadcast system using principal component analysis (PCA). Therefore, the number of RF chains needed in massive MU-MIMO is reduced by removing the antennas that contribute least to the system sum capacity. A precoding technique of Zero Forcing is used and each user is equipped with a single antenna. Our simulation results show that the proposed antenna selection technique performs much better than mean channel gain selection.
机译:大规模多用户多输入多输出(MU-MIMO)是新兴的第五代(5G)无线通信技术。但是,大规模MIMO中基站(BS)所需的大量天线和射频(RF)链的部署带来了高系统复杂性和硬件能耗的挑战。通过使用Kronecker信道建模,开发了一种窄带信道的简单随机MIMO模型,该模型使用了移动站(MS)和BS的相关矩阵。在本文中,针对使用主成分分析(PCA)的MU-MIMO广播系统中的Kronecker信道建模,提出了两种用于实际天线选择的半启发式技术。因此,通过去除对系统总容量贡献最小的天线,可以减少大规模MU-MIMO中所需的RF链数量。使用了零强制的预编码技术,并且每个用户都配备了一个天线。我们的仿真结果表明,所提出的天线选择技术比平均信道增益选择要好得多。

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