利用 1 位 ADC 增强大规模 MIMO 的数据检测功能

Amin Radbord, Italo Atzeni, Antti Tolli
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引用次数: 0

摘要

软估计符号的预期值(即在线性组合之后和数据检测之前)最近在多个用户设备(UE)和基站最大比值组合(MRC)接收机上得到了表征。在本文中,我们首先对具有相关雷利衰落的多用户设备(UE)环境下的零强迫(ZF)和最小均方误差(MMSE)接收器的软估计符号预期值进行了数值评估。然后,我们提出了一种联合数据检测(JD)策略,该策略利用了干扰 UE 的软估计符号之间的相互依赖性,以及其低复杂度变体。这些策略与将最大似然数据检测适应于 1 位量化的天真方法进行了比较。数值结果表明,就符号错误率而言,ZF 和 MMSE 比 MRC 有相当大的提高。此外,与单 UE 数据检测相比,所提出的 JD 及其低复杂度变体也有显著提升。
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Enhanced data Detection for Massive MIMO with 1-Bit ADCs
We present new insightful results on the uplink data detection for massive multiple-input multiple-output systems with 1-bit analog-to-digital converters. The expected values of the soft-estimated symbols (i.e., after the linear combining and prior to the data detection) have been recently characterized for multiple user equipments (UEs) and maximum ratio combining (MRC) receiver at the base station. In this paper, we first provide a numerical evaluation of the expected value of the soft-estimated symbols with zero-forcing (ZF) and minimum mean squared error (MMSE) receivers for a multi-UE setting with correlated Rayleigh fading. Then, we propose a joint data detection (JD) strategy, which exploits the interdependence among the soft-estimated symbols of the interfering UEs, along with its low-complexity variant. These strategies are compared with a naive approach that adapts the maximum-likelihood data detection to the 1-bit quantization. Numerical results show that ZF and MMSE provide considerable gains over MRC in terms of symbol error rate. Moreover, the proposed JD and its low-complexity variant provide a significant boost in comparison with the single-UE data detection.
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