The deployment of large-scale antenna arrays for cellular base stations (BSs), termed as `Massive MIMO', has been a key enabler for meeting the ever-increasing capacity requirement for 5G communication systems and beyond. Despite their promising performance, fully-digital massive MIMO systems require a vast amount of hardware components including radio frequency chains, power amplifiers, digital-to-analog converters (DACs), etc., resulting in a huge increase in terms of the total power consumption and hardware costs for cellular BSs. Towards both spectrally-efficient and energy-efficient massive MIMO deployment, a number of hardware limited architectures have been proposed, including hybrid analog-digital structures, constant-envelope transmission, and use of low-resolution DACs. In this paper, we overview the recent interest in improving the error-rate performance of massive MIMO systems deployed with 1-bit DACs through precoding at the symbol level. This line of research goes beyond traditional interference suppression or cancellation techniques by managing interference on a symbol-by-symbol basis. This provides unique opportunities for interference-aware precoding tailored for practical massive MIMO systems. Firstly, we characterize constructive interference (CI) and elaborate on how CI can benefit the 1-bit signal design by exploiting the traditionally undesired multi-user interference as well as the interference from imperfect hardware components. Subsequently, we overview several solutions for 1-bit signal design to illustrate the gains achievable by exploiting CI. Finally, we identify some challenges and future research directions for 1-bit massive MIMO systems that are yet to be explored.
翻译:为蜂窝基站部署称为“Massive MIMO”的大型天线阵列,是满足5G通信系统及其他系统不断增加的能力需求的关键推动因素。尽管这些天线阵列的表现令人充满希望,但完全数字规模的MIMO系统需要大量硬件组件,包括无线电频率链、电力放大器、数字到模拟转换器等,导致蜂窝BS总电耗和硬件成本的大幅增长。为了实现光谱高效和节能的大规模MIMO部署,提出了一些硬件有限的总体结构,包括混合的模拟-数字结构、恒星传输和使用低分辨率的DACs。我们本文概述了最近希望通过符号级的预编码改进大型IMO系统的错误率性能。这一研究范围超越了传统的干扰抑制或取消技术,通过对大规模比喻基础的干扰加以管理,从而提供了一些硬件有限的结构概览,包括混合的模拟-数字结构、恒定的传输以及使用低分辨率的DIMO系统。我们从一些干扰-预兆化的图像化了IMIMI的模型设计,最终将IMO系统加以利用。