摘要翻译：
分析了大规模多输入多输出(MIMO)系统中基站采用低分辨率模数转换器时的上行链路性能。设计了一种同时考虑加性高斯白噪声(AWGN)和量化噪声的高性能MMSE接收机，该接收机适用于均匀分辨率ADC和非均匀分辨率ADC。对于所提出的MMSE接收机，我们利用随机矩阵理论推导出系统上行链路频谱效率(SE)的渐近等价。数值结果表明，采用低分辨率ADC的massive MIMO系统，通过增加基站天线数目，仍能获得令人满意的上行链路SE，且上行链路SE的渐近等价是紧密的。
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英文标题：
《Performance Analysis of Massive MIMO with Low-Resolution ADCs》
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作者：
Chao Wei, Zaichen Zhang
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最新提交年份：
2017
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分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Signal Processing        信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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英文摘要：
  The uplink performance of massive multiple-input-multiple-output (MIMO) systems where the base stations (BS) employ low-resolution analog-to-digital converters (ADCs) is analyzed. A high performance MMSE receiver that takes both additive white Gaussian noise (AWGN) and quantization noise into consideration is designed, which works well for both cases of uniform resolution ADCs and non-uniform resolution ADCs. With the proposed MMSE receiver, we then employ the random matrix theory to derive the asymptotic equivalent of the uplink spectral efficiency (SE) of the system. Numerical results show the tightness of the asymptotic equivalent of the uplink SE, and massive MIMO with low-resolution ADCs can still achieve the satisfying uplink SE by increasing the number of antennas at BS.
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PDF链接：
https://arxiv.org/pdf/1711.10739