论文标题
2D梁域统计CSI估计大量MIMO上行链路
2D Beam Domain Statistical CSI Estimation for Massive MIMO Uplink
论文作者
论文摘要
在本文中，我们研究了大型MIMO系统中基于二维（2D）基于光束的统计通道模型（BSCM）的梁域统计通道状态信息（CSI）估计。问题是根据基于梁域通道功率矩阵（BDCPM）的问题，该问题基于基于多个接收试验的飞行员信号。接收模型显示了接收试点信号的统计属性与BDCPM之间的关系，源自2D-BSCM。根据接收模型，我们通过kullback-leibler（KL）差异提出了优化问题。通过解决优化问题，提出了一种新的估计统计CSI的新方法，而无需涉及瞬时CSI。所提出的方法的复杂性要比MMV局灶性不确定的系统求解器（M-cocuss）算法低得多。我们通过利用算法中特定矩阵的循环结构进一步降低了所提出的方法的复杂性。我们还通过引入另一个应用程序展示了该方法的一般性。仿真结果表明，该方法在通道估计中使用时效果很好，并带来显着的性能增长。
In this paper, we investigate the beam domain statistical channel state information (CSI) estimation for the two dimensional (2D) beam based statistical channel model (BSCM) in massive MIMO systems.The problem is to estimate the beam domain channel power matrices (BDCPMs) based on multiple receive pilot signals. A receive model shows the relation between the statistical property of the receive pilot signals and the BDCPMs is derived from the 2D-BSCM. On the basis of the receive model,we formulate an optimization problem with the Kullback-Leibler (KL) divergence. By solving the optimization problem, a novel method to estimate the statistical CSI without involving instantaneous CSI is proposed. The proposed method has much lower complexity than the MMV focal underdetermined system solver (M-FOCUSS) algorithm. We further reduce the complexity of the proposed method by utilizing the circulant structures of particular matrices in the algorithm. We also showed the generality of the proposed method by introducing another application. Simulations results show that the proposed method works well and bring significant performance gain when used in channel estimation.
