空间非平稳大规模 MIMO 系统中采用抖动量化信号的插入式信道估计
Plug-in Channel Estimation with Dithered Quantized Signals in Spatially Non-Stationary Massive MIMO Systems
AI总结：
针对空间非平稳大规模 MIMO 的一比特量化接收，本文提出带抖动的插入式 BLMMSE 信道估计、协方差失真分析、角域非负最小二乘拟合及 BLMMSE 接收机，性能逼近理想协方差方案。
摘要：
随着大规模 MIMO 系统的阵列维度增长到前所未有的水平，出现了两个问题。首先，沿天线单元的空间平稳性假设不再成立。其次，如果使用高分辨率模数转换器，较大的阵列尺寸会导致难以接受的高功耗。为应对这两个挑战，我们针对配备一比特量化器且具有空间非平稳信道的大规模大规模 MIMO 系统，考虑了一种基于 Bussgang 线性最小均方误差（BLMMSE）的信道估计器。其他工作通常假设基站已知信道协方差，而我们考虑一种插入式 BLMMSE 估计器，它使用信道协方差的估计值，并严格分析由于使用估计协方差而非真实协方差所产生的失真。为处理空间非平稳性，我们在量化信号中引入抖动，并给出理论误差分析。此外，我们提出一种角域拟合过程，该过程基于求解一个非负最小二乘实例。对于多用户数据传输阶段，我们进一步提出一种基于 BLMMSE 的接收机，以处理一比特量化的数据信号。数值结果表明，所提出的 BLMMSE 信道估计器的性能非常接近具有信道协方差矩阵理想知识的 oracle 辅助方案。就所得遍历和速率而言，BLMMSE 接收机优于传统的最大比合并和迫零接收机。
英文摘要：
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 First, the spatial stationarity assumption along the antenna elements is no longer valid.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.
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