This work investigates the downlink performance of a multi-cell massive multiple-input multiple-output (MIMO) system that employs one-bit analog-to-digital converters (ADCs) and digital-to-analog converters (DACs) in the receiving and transmitting radio frequency (RF) chains at each base station (BS) in order to reduce the power consumption. We utilize Bussgang decomposition to derive the minimum mean squared error (MMSE) channel estimates at each BS based on the quantized received uplink training signals, and the asymptotic closed-form expressions of the achievable downlink rates under one-bit quantized zero-forcing (ZF) precoding implemented using the estimated channels. The derived expressions explicitly show the impact of quantization noise, thermal noise, pilot contamination, and interference, and are utilized to study the number of additional antennas needed at each BS of the one-bit MIMO system to perform as well as the conventional MIMO system. Numerical results verify our analysis, and reveal that despite needing more antennas to achieve the same sum average rate, the one-bit massive MIMO system is more energy-efficient than the conventional system, especially at high sampling frequencies.

翻译：本文研究了一种采用单比特模数转换器（ADC）和数模转换器（DAC）的多小区大规模多输入多输出（MIMO）系统的下行链路性能，其中这些转换器分别用于每个基站（BS）的接收与发射射频（RF）链路，以降低功耗。我们利用Bussgang分解方法，基于量化后的上行训练接收信号推导出每个基站的最小均方误差（MMSE）信道估计，并得到使用估计信道实现的单比特量化迫零（ZF）预编码下可达下行速率的渐近闭式表达式。所推导的表达式明确展示了量化噪声、热噪声、导频污染和干扰的影响，并用于研究单比特MIMO系统中每个基站需要额外增加多少天线才能达到与传统MIMO系统相当的性能。数值结果验证了我们的分析，并揭示出尽管需要更多天线才能实现相同的总平均速率，但单比特大规模MIMO系统比传统系统具有更高的能量效率，特别是在高采样频率下。