As the array dimension of massive MIMO systems increases to unprecedented levels, two problems occur. First, the spatial stationarity assumption along the antenna elements is no longer valid. Second, the large array size results in an unacceptably high power consumption if high-resolution analog-to-digital converters are used. To address these two challenges, we consider a Bussgang linear minimum mean square error (BLMMSE)-based channel estimator for large scale massive MIMO systems with one-bit quantizers and a spatially non-stationary channel. Whereas other works usually assume that the channel covariance is known at the base station, we consider a plug-in BLMMSE estimator that uses an estimate of the channel covariance and rigorously analyze the distortion produced by using an estimated, rather than the true, covariance. To cope with the spatial non-stationarity, we introduce dithering into the quantized signals and provide a theoretical error analysis. In addition, we propose an angular domain fitting procedure which is based on solving an instance of non-negative least squares. For the multi-user data transmission phase, we further propose a BLMMSE-based receiver to handle one-bit quantized data signals. Our numerical results show that the performance of the proposed BLMMSE channel estimator is very close to the oracle-aided scheme with ideal knowledge of the channel covariance matrix. The BLMMSE receiver outperforms the conventional maximum-ratio-combining and zero-forcing receivers in terms of the resulting ergodic sum rate.

翻译：随着大规模MIMO系统阵列维度达到前所未有的水平，两个问题随之出现。首先，天线单元沿阵列的空间平稳性假设不再成立；其次，若使用高分辨率模数转换器，大阵列尺寸将导致功耗过高。针对这些挑战，本文提出一种基于Bussgang线性最小均方误差（BLMMSE）的信道估计器，适用于采用单比特量化器且信道具有空间非平稳性的大规模MIMO系统。与通常假设基站已知信道协方差的其他研究不同，我们考虑一种利用估计信道协方差的可接入BLMMSE估计器，并严格分析了使用估计协方差而非真实协方差所引入的失真。为应对空间非平稳性，我们在量化信号中引入抖动，并给出理论误差分析。此外，我们提出一种基于非负最小二乘问题求解的角度域拟合方法。在多用户数据传输阶段，我们进一步提出基于BLMMSE的接收机以处理单比特量化数据信号。数值结果表明，所提BLMMSE信道估计器的性能与具有理想信道协方差矩阵先验知识的辅助方案非常接近。在遍历和速率方面，BLMMSE接收机优于传统最大比合并和迫零接收机。