摘要翻译：
本文提出了一种具有分布式处理功能的massive MIMO基站的可扩展模块化体系结构。当每个节点处理所有额外涉及的处理时，可以通过添加新节点来容易地添加新天线。该体系结构支持共轭波束形成、迫零和MMSE，其中对于后两种情况需要中心矩阵求逆。该矩阵求逆所需时间的影响与一般帧格式一起仔细分析。作为贡献的一部分，提出了仔细的计算，内存和通信分析。结果表明，所有计算都可以映射到单个计算结构，由单个这样的处理单元组成的处理节点可以处理宽范围和多个终端。
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英文标题：
《A Distributed Processing Architecture for Modular and Scalable Massive
  MIMO Base Stations》
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作者：
Erik Bertilsson, Oscar Gustafsson, Erik G. Larsson
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最新提交年份：
2018
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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：
  In this work, a scalable and modular architecture for massive MIMO base stations with distributed processing is proposed. New antennas can readily be added by adding a new node as each node handles all the additional involved processing. The architecture supports conjugate beamforming, zero-forcing, and MMSE, where for the two latter cases a central matrix inversion is required. The impact of the time required for this matrix inversion is carefully analyzed along with a generic frame format. As part of the contribution, careful computational, memory, and communication analyses are presented. It is shown that all computations can be mapped to a single computational structure and that a processing node consisting of a single such processing element can handle a broad range of bandwidths and number of terminals.
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PDF链接：
https://arxiv.org/pdf/1801.07967