基于距离保持构造性的符号级预编码设计 干扰区域

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摘要翻译：
本文研究了多用户多输入单输出(MISO)信道下行链路的符号级预编码(SLP)设计问题。我们考虑任意形状和大小的一般星座，并将我们自己限制在一个主要类别的相长干涉区(CIR)中，即距离保持CIR(DPCIR)。我们对DPCIRs进行了全面的研究，并导出了这些区域的一些性质。利用这些性质，我们首先证明了给定DPCIR中的任何信号的范数大于或等于对应星座点的范数当且仅当星座的凸壳包含原点。然后证明了DPCIR上的无噪声接收信号的功率是与无限大Voronoi边有关的两个参数的单调严格增函数。利用DPCIRs的凸描述及其性质，我们提出了两个设计问题，即带信干噪比(SINR)约束的SLP功率最小化问题和最大最小公平准则下的SLP SINR平衡问题。基于DPCIRs的SLP功率最小化可以直接写成一个二次程序(QP)。我们给出了这个问题的一个简化的重新表述，它的计算复杂性较小。然而，SLP最大最小SINR在其原始形式中是非凸的，因此很难处理。我们提出了几种可供选择的优化方法，包括半定程序(SDP)公式和块坐标下降(BCD)优化。我们通过大量的仿真结果讨论和评估了由于所提出的替代方法造成的损失。
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英文标题：
《Symbol-Level Precoding Design Based on Distance Preserving Constructive
  Interference Regions》
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作者：
Alireza Haqiqatnejad, Farbod Kayhan and Bjorn Ottersten
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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：
  In this paper, we investigate the symbol-level precoding (SLP) design problem in the downlink of a multiuser multiple-input single-output (MISO) channel. We consider generic constellations with any arbitrary shape and size, and confine ourselves to one of the main categories of constructive interference regions (CIR), namely, distance preserving CIR (DPCIR). We provide a comprehensive study of DPCIRs and derive some properties for these regions. Using these properties, we first show that any signal in a given DPCIR has a norm greater than or equal to the norm of the corresponding constellation point if and only if the convex hull of the constellation contains the origin. It is followed by proving that the power of the noiseless received signal lying on a DPCIR is a monotonic strictly increasing function of two parameters relating to the infinite Voronoi edges. Using the convex description of DPCIRs and their properties, we formulate two design problems, namely, the SLP power minimization with signal-to-interference-plus-noise ratio (SINR) constraints, and the SLP SINR balancing problem under max-min fairness criterion. The SLP power minimization based on DPCIRs can straightforwardly be written as a quadratic program (QP). We provide a simplified reformulation of this problem which is less computationally complex. The SLP max-min SINR, however, is non-convex in its original form, and hence difficult to tackle. We propose several alternative optimization approaches, including semidefinite program (SDP) formulation and block coordinate descent (BCD) optimization. We discuss and evaluate the loss due to the proposed alternative methods through extensive simulation results.
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PDF链接：
https://arxiv.org/pdf/1804.0093

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