To solve practical challenges for implementing deep learning-based algorithm in MIMO signal detector such as handling complex number or designing proper neural network for a specific communication system, (Baek et al. , 2019) has proposed candidate implementation methodologies with simple verification experiments. According to (Baek et al. , 2019), it was shown that the proposed algorithms can achieve the optimal ML performance. However, due to the lack of explanation on the experimental environment, it is difficult for readers to reproduce the presented experiments and obtain the same results. This document precisely explains on the experimental environments of (Baek et al. , 2019) including the exact channel profiles.

中文翻译：

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对“传统的MIMO发射机基于深度学习的信号检测实现方法”实验环境的补充说明

为了解决在MIMO信号检测器中实施基于深度学习的算法的实际挑战，例如处理复数或为特定的通信系统设计适当的神经网络，（Baek 等。 （2019年）提出了带有简单验证实验的候选者实施方法。根据（白等。 ，2019），结果表明所提出的算法可以实现最佳的机器学习性能。但是，由于缺乏对实验环境的解释，读者很难重现给出的实验并获得相同的结果。本文档准确地解释了（Baek等。 （2019年），包括确切的渠道资料。