摘要翻译：
利用大量连续的实验数据，研究了窄带无线身体对身体网络中广泛意义平稳性(WSS)在“日常”场景下的存在性。我们使用不同的参数和非参数假设检验来评估从不同的人体传感器位置发现的几个人体到人体通道的均值和方差平稳性以及分布一致性。我们还估计功率谱的变化来评价自协方差函数的时间独立性。我们的结果表明，在95%的置信度下，对于不同禁令中心之间的通道，窗口长度为5秒的情况，最多90%满足WSS假设。此外，在最佳情况下，在超过10秒的较长窗口长度内，hub-to-hub通道保持相当稳定（满足零假设的概率超过80%）。体-体信道的短时功率谱变化也可以忽略不计。此外，我们还表明，身体到身体的通道可以被认为是广义平稳的，在比身体上的通道更长的时间内。
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英文标题：
《Wide-Sense-Stationarity of Everyday Wireless Channels for Body-to-Body
  Networks》
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作者：
Samiya M. Shimly, David B. Smith and Samaneh Movassaghi
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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：
  The existence of wide-sense-stationarity (WSS) in narrowband wireless body-to-body networks is investigated for "everyday" scenarios using many hours of contiguous experimental data. We employ different parametric and non-parametric hypothesis tests for evaluating mean and variance stationarity, along with distribution consistency, of several body-to-body channels found from different on-body sensor locations. We also estimate the variation of power spectrum to evaluate the time independence of the auto-covariance function. Our results show that, with 95% confidence, the assumption of WSS is met for at most 90% of the cases with window lengths of 5 seconds for the channels between the hubs of different BANs. Additionally, in the best-case scenario, the hub-to-hub channel remains reasonably stationary (with more than 80% probability of satisfying the null hypothesis) for longer window lengths of more than 10 seconds. The short time power spectral variation for body-to-body channels is also shown to be negligible. Moreover, we show that body-to-body channels can be considered wide-sense-stationary over significantly longer periods than on-body channels.
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PDF链接：
https://arxiv.org/pdf/1803.05592