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Joint user grouping and beamforming for low complexity massive MIMO systems

机译:低复杂度大规模MIMO系统的联合用户分组和波束成形

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In massive MIMO systems, to partition users into groups and serve the groups separately can significantly reduce the processing complexity. In the existing literature, user grouping is done by classifying the channel covariance matrices. Consequently, the inter-group interference due to user grouping and per group processing is not taken into account. In addition, those methods only work for a fixed number of groups, and the optimal group number is hard to determine. In this paper, a joint user grouping and beamforming strategy is proposed to jointly optimize the number of groups, the user grouping, and the beamforming. The scheme is derived by maximizing the total expected signal-to-interference-leakage-and-noise-ratio (SLNR) lower bound in the network via two-timescale stochastic optimization techniques. Numerical results demonstrate significant sum rate performance gain over the baseline scheme in the literature.
机译:在大规模MIMO系统中,将用户划分为组并分别为组提供服务可以显着降低处理复杂性。在现有文献中,通过对信道协方差矩阵进行分类来完成用户分组。因此,不考虑由于用户分组和按组处理而引起的组间干扰。另外,这些方法仅适用于固定数量的组,并且最佳组号难以确定。在本文中,提出了一种联合用户分组和波束成形策略,以共同优化组数,用户分组和波束成形。该方案是通过两次时间尺度随机优化技术最大化网络中的总预期信号干扰干扰噪声比(SLNR)下限而得出的。数值结果表明,与文献中的基准方案相比,总和率性能得到了显着提高。

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