大规模多输入多输出（MIMO）技术是公认的5G关键技术之一，但其在实际应用中仍面临成本过高、功耗过大等瓶颈。在大规模MIMO系统中采用低分辨率模数转换器（ADC）来取代传统的高分辨率ADC，成为解决这一瓶颈问题的有效方案之一。然而，低分辨率ADC不可避免地引入非线性失真效应，降低系统性能。为此，本项目将考虑低分辨率ADC的非线性失真，以高维随机矩阵、信息论、压缩感知和凸优化为理论工具，构建基于低分辨率ADC的大规模MIMO系统理论框架。首先，推导系统频谱效率和能量效率的准确表达式，并设计信道容量可达的最优发射信号分布；其次，综合考虑系统导频污染、非理想信道状态信息、空间受限、相位噪声和功放失真等非理想因素的性能，揭示制约系统性能的关键因素；最后，结合毫米波技术，分析系统在具有稀疏性和频率选择性的毫米波信道下可达性能界。本项目可为满足5G高谱效高能效的大规模MIMO系统实际部署提供理论指导。

Massive MIMO technology has become one of the key technologies for 5G. However, the high cost and power consumption bottleneck has not been solved in massive MIMO systems. One of the effective solutions to these bottlenecks is to deploy low-resolution ADCs instead of high-resolution ADCs in massive MIMO systems. However, the nonlinear distortion caused by low-resolution ADCs decreases the system performance significantly. Therefore, we will consider the nonlinear distortion caused by low-resolution ADCs and investigate the fundamental theory of massive MIMO systems with low-resolution ADCs by using the tools of high-dimension random matrix, information theory, compress sensing, and convex theory. First, we will derive the exact, closed-form expressions of spectral and energy efficiency, and design the capacity-achievable optimum transmit signal distribution. Then, we will study the key facts and theory of limiting the system performance under imperfect conditions, such as pilot contamination, imperfect channel state information, space constrain, phase noise, and power amplifier distortion. Finally, with the mmWave technology, we will analysis the achievable performance bounds of massive MIMO systems over sparse and frequency-selective mmWave channels. The purpose of this project is to provide theoretical instructions for practical massive MIMO systems, which fulfill the requirement of high spectral and energy efficiency of 5G.