Referring to the system equipped with single-bit converters, 1-bit mmWave communications is gaining increasing attention for its superb cost efficiency. However, the inherent non-linear distortion renders the detectors designed for classical transparent communications inapplicable, leading to an urgent need for novel detecting solutions dedicated to 1-bit systems. Although a few endeavours have been made towards learning-based (as opposed to the traditional model-based ) detectors for multi-user (MU) 1-bit systems, they are exclusively limited to narrowband channels and fail to cope with the multi-path effects inevitable to mmWave systems. In this paper, we first design a learning-based detector (LeaD) for general wideband multi-user (wMU) scenarios. Though stemming from block-based detection, the classic workhorse for transparent systems, LeaD faces either unaffordable complexity or unacceptable data rate in 1-bit systems. Given the impracticability of block-based detection, we resort to the serial detection mechanism and henceforth devise a so-termed model-enhanced (Me-)LeaD by utilizing the channel delay-domain information. Me-LeaD can be further augmented by exploiting the channel angular-domain information. Underpinned by a judiciously tailored method for extracting tbe model information, the proposed Me-LeaD demonstrates a decent overall performance in general 1-bit wMU scenarios.

中文翻译：

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用于宽带多用户 1 位毫米波通信的基于模型增强学习的检测器 (Me-LeaD)

参考配备单位转换器的系统，1 位毫米波通信因其卓越的成本效率而越来越受到关注。然而，固有的非线性失真使得为经典透明通信设计的检测器不适用，导致迫切需要专用于 1 位系统的新型检测解决方案。虽然做了一些努力以学习为基础（相对于传统的 用于多用户 (MU) 1 位系统的基于模型的）检测器，它们仅限于窄带信道，无法应对毫米波系统不可避免的多径效应。在本文中，我们首先为一般宽带多用户 (wMU) 场景设计了一个基于学习的检测器 (LeaD)。尽管源于基于块的检测，透明系统的经典主力，LeaD 在 1 位系统中面临着难以承受的复杂性或无法接受的数据速率。鉴于基于块的检测的不切实际，我们采用串行检测机制，并因此设计了一种利用信道延迟域信息的所谓模型增强（Me-）LeaD。Me-LeaD 可以通过利用通道角域信息进一步增强。以明智地定制的方法为基础，用于提取模型信息，