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雷达卡
摘要翻译：
在大规模多用户多输入多输出（MU-MIMO）基站(BS)中，数模转换器的功耗占总功耗的很大比例。使用1位DAC可以显著降低功耗。本文研究了MU-MIMO下行链路系统的预编码问题。在这样的系统中，预编码问题起着核心作用，因为预编码符号受到1位DAC引入的额外失真的影响。本文基于交替方向法框架，提出了一种高效的非线性预编码算法。与经典算法（如半定松弛(SDR)和平方无穷范数Douglas-Rachford分裂(SQUID)算法）解决原预编码问题的凸松弛版本不同，新算法直接解决原非凸问题。新算法在一些温和的条件下保证了全局收敛性。导出了其收敛性的一个充分条件。在不同条件下的实验结果表明，新算法可以达到与SDR算法相当的最先进的精度，同时效率也要高得多（比SDR算法快300倍以上）。
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英文标题：
《Efficient Nonlinear Precoding for Massive MU-MIMO Downlink Systems with
1-Bit DACs》
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作者：
Lei Chu, Fei Wen, Lily Li, and Robert Qiu
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最新提交年份：
2019
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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：Mathematics 数学
二级分类：Optimization and Control 优化与控制
分类描述：Operations research, linear programming, control theory, systems theory, optimal control, game theory
运筹学，线性规划，控制论，系统论，最优控制，博弈论
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英文摘要：
The power consumption of digital-to-analog converters (DACs) constitutes a significant proportion of the total power consumption in a massive multiuser multiple-input multiple-output (MU-MIMO) base station (BS). Using 1-bit DACs can significantly reduce the power consumption. This paper addresses the precoding problem for the massive narrow-band MU-MIMO downlink system equipped with 1-bit DACs at each BS. In such a system, the precoding problem plays a central role as the precoded symbols are affected by extra distortion introduced by 1-bit DACs. In this paper, we develop a highly-efficient nonlinear precoding algorithm based on the alternative direction method framework. Unlike the classic algorithms, such as the semidefinite relaxation (SDR) and squared-infinity norm Douglas-Rachford splitting (SQUID) algorithms, which solve convex relaxed versions of the original precoding problem, the new algorithm solves the original nonconvex problem directly. The new algorithm is guaranteed to globally converge under some mild conditions. A sufficient condition for its convergence has been derived. Experimental results in various conditions demonstrated that, the new algorithm can achieve state-of-the-art accuracy comparable to the SDR algorithm, while being much more efficient (more than 300 times faster than the SDR algorithm).
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PDF链接：
https://arxiv.org/pdf/1804.08839
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