摘要翻译：
第五代(5G)蜂窝系统将基于海量多用户(MU)、多输入多输出(MIMO)技术来实现高频谱效率。然而，在基站(BS)拥有数百个天线和射频(RF)链需要高得令人望而却步的硬件成本和功率消耗。针对MU-MIMO下行链路，提出了一种新的非线性预编码算法，其中每个RF链包含一个8相（3位）恒模发射机，使得使用低成本、低功耗的模拟硬件成为可能。我们提出了一种高通量的VLSI结构，并给出了在Xilinx Virtex-7 FPGA上的实现结果。与最近报道的每条RF链使用两个1位数模转换器的BS设计的非线性预编码器相比，我们的设计在FPGA资源增加不超过2.7倍的情况下实现了高达3.75 dB的发射功率降低。
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英文标题：
《VLSI Design of a 3-bit Constant-Modulus Precoder for Massive MU-MIMO》
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作者：
Oscar Casta\~neda, Sven Jacobsson, Giuseppe Durisi, Tom Goldstein,
  Christoph Studer
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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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一级分类：Computer Science        计算机科学
二级分类：Information Theory        信息论
分类描述：Covers theoretical and experimental aspects of information theory and coding. Includes material in ACM Subject Class E.4 and intersects with H.1.1.
涵盖信息论和编码的理论和实验方面。包括ACM学科类E.4中的材料，并与H.1.1有交集。
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一级分类：Mathematics        数学
二级分类：Information Theory        信息论
分类描述：math.IT is an alias for cs.IT. Covers theoretical and experimental aspects of information theory and coding.
它是cs.it的别名。涵盖信息论和编码的理论和实验方面。
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英文摘要：
  Fifth-generation (5G) cellular systems will build on massive multi-user (MU) multiple-input multiple-output (MIMO) technology to attain high spectral efficiency. However, having hundreds of antennas and radio-frequency (RF) chains at the base station (BS) entails prohibitively high hardware costs and power consumption. This paper proposes a novel nonlinear precoding algorithm for the massive MU-MIMO downlink in which each RF chain contains an 8-phase (3-bit) constant-modulus transmitter, enabling the use of low-cost and power-efficient analog hardware. We present a high-throughput VLSI architecture and show implementation results on a Xilinx Virtex-7 FPGA. Compared to a recently-reported nonlinear precoder for BS designs that use two 1-bit digital-to-analog converters per RF chain, our design enables up to 3.75 dB transmit power reduction at no more than a 2.7x increase in FPGA resources.
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PDF链接：
https://arxiv.org/pdf/1803.00558