摘要翻译：
本文在6 GHz以上的室内外环境中，建立了一个基于超额损耗的多径分量交叉极化比(XPR)模型。这些结果是基于在15到80 GHz的几个频段内进行的28次测量活动。一个传统的MPC的XPR模型假设一个恒定的平均值非常不适合我们的测量，而且高估了去极化效应。我们的测量揭示了一个明显的趋势，即相对于自由空间路径损耗而言，MPC XPR与超额损耗成反比。该模型在物理上是合理的，因为更高的超额损耗归因于更多的有损相互作用或与物体的更多相互作用，导致更大的去极化机会。此外，测量结果表明MPC XPR对频率和环境的依赖性不强。在我们的MPC XPR模型中，一个零分贝超额损耗的MPC的平均XPR为28分贝。当超额损耗每增加一分贝时，平均XPR减小半分贝，平均XPR附近的标准差为6分贝。该模型适用于现有的信道模型，以再现上述6-GHz无线链路的真实MPC XPRs。
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英文标题：
《Modeling the Multipath Cross-Polarization Ratio for Above-6 GHz Radio
  Links》
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作者：
Aki Karttunen, Jan J\"arvel\"ainen, Sinh Le Hong Nguyen, and Katsuyuki
  Haneda
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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 parameterize an excess loss-based multipath component (MPC) cross-polarization ratio (XPR) model in indoor and outdoor environments for above-6 GHz frequency bands. The results are based on 28 measurement campaigns in several frequency bands ranging from 15 to 80 GHz. A conventional XPR model of an MPC assuming a constant mean value fits our measurements very poorly and moreover overestimates the depolarization effect. Our measurements revealed a clear trend that the MPC XPR is inversely proportional to an excess loss in reference to the free-space path loss. The model is physically sound as a higher excess loss is attributed to more lossy interactions or to a greater number of interactions with objects, leading to a greater chance of depolarization. The measurements furthermore showed that the MPC XPR is not strongly frequency or environment dependent. In our MPC XPR model, an MPC with zero-dB excess loss has a mean XPR of 28 dB. The mean XPR decreases half-a-dB as the excess loss increases by every dB and the standard deviation around the mean is 6 dB. The model is applicable to existing channel models to reproduce realistic MPC XPRs for the above 6-GHz radio links.
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PDF链接：
https://arxiv.org/pdf/1804.00847