In this paper, the problem of pilot beam pattern design for channel
estimation in massive multiple-input multiple-output systems with a large
number of transmit antennas at the base station is considered, and a new
algorithm for pilot beam pattern design for optimal channel estimation is
proposed under the assumption that the channel is a stationary Gauss-Markov
random process. The proposed algorithm designs the pilot beam pattern
sequentially by exploiting the properties of Kalman filtering and the
associated prediction error covariance matrices and also the channel statistics
such as spatial and temporal channel correlation. The resulting design
generates a sequentially-optimal sequence of pilot beam patterns with low
complexity for a given set of system parameters. Numerical results show the
effectiveness of the proposed algorithm.

本研究提出了一种新的算法来针对大规模多输入多输出系统中基站的大量发射天线进行信道估计时的导频波束设计问题，该算法依据信道被假定成是一种平稳的高斯 - 马尔科夫随机过程，并通过利用卡尔曼滤波及其相关的预测误差协方差矩阵的性质以及信道统计信息 (如空间和时间信道相关性) 顺序地设计导频波束模式，从而生成给定系统参数下的序贯最优导频波束序列，且具有较低的复杂度。数值结果表明该算法表现良好。