Robust massive MIMO equilization for mmWave systems with low resolution ADCs

Kilian Roth, J. Nossek
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引用次数: 3

Abstract

Leveraging the available millimeter wave spectrum will be important for 5G. In this work, we investigate the performance of digital beamforming with low resolution Analog-to-Digital-Converters based on link level simulations including channel estimation, Multiple Input Multiple Output (MIMO) equalization and channel decoding. We consider the recently agreed 3GPP NR type 1 Orthogonal Frequency Division Multiplexing (OFDM) reference signals. The comparison shows sequential Dichotomous Coordinate Descent (DCD) outperforms Minimum Mean Square Error (MMSE)-based MIMO equalization both in terms of detection performance and complexity. We also show that the DCD based algorithm is more robust to channel estimation errors. In contrast to the common believe we also show that the complexity of MMSE equalization for a massive MIMO system is not dominated by the matrix inversion but by the computation of the Gram matrix.
具有低分辨率adc的毫米波系统的鲁棒大规模MIMO均衡
利用可用的毫米波频谱对5G至关重要。在这项工作中,我们研究了基于链路级仿真的低分辨率模数转换器的数字波束形成性能,包括信道估计、多输入多输出(MIMO)均衡和信道解码。我们考虑最近商定的3GPP NR类型1正交频分复用(OFDM)参考信号。对比表明,顺序二分类坐标下降(DCD)在检测性能和复杂度方面都优于基于最小均方误差(MMSE)的MIMO均衡。我们还证明了基于DCD的算法对信道估计误差具有更强的鲁棒性。与通常的看法相反,我们还表明,大规模MIMO系统的MMSE均衡的复杂性不是由矩阵反转决定的,而是由Gram矩阵的计算决定的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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