摘要翻译：
纳米技术的发展为物联网（IoT）提供了新的能力，可以通过部署小到几百纳米的传感器来监测极其细粒度的事件。研究人员预测，这种微小的传感器可以使用太赫兹波段（0.1-10太赫兹）辐射的石墨烯纳米天线传输无线数据。然而，用纳米级的能量供应来为这种无线通信供电是一个需要克服的主要挑战。在本文中，我们提出了一个能量有效的事件监测框架的纳米物联网，使纳米传感器可以更新远程基站的位置和类型的检测事件只使用一个短脉冲。纳米传感器在整个太赫兹频段上使用不同的中心频率和不重叠的半功率带宽来编码不同的事件。利用均匀线阵(ULA)天线，基站通过估计脉冲的到达方向来定位事件，并从接收信号的频谱质心估计的中心频率中对事件进行分类。仿真结果表明，在距离1米的地方，一个6阶导数高斯脉冲仅消耗1阿托焦耳，就可以获得1.58度的定位精度和98.8%的分类精度。
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英文标题：
《Energy Efficient Event Localization and Classification for Nano IoT》
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作者：
Shree Prasad M. and Trilochan Panigrahi and Mahbub Hassan
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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：
  Advancements in nanotechnology promises new capabilities for Internet of Things (IoT) to monitor extremely fine-grained events by deploying sensors as small as a few hundred nanometers. Researchers predict that such tiny sensors can transmit wireless data using graphene-based nano-antenna radiating in the terahertz band (0.1-10 THz). Powering such wireless communications with nanoscale energy supply, however, is a major challenge to overcome. In this paper, we propose an energy efficient event monitoring framework for nano IoT that enables nanosensors to update a remote base station about the location and type of the detected event using only a single short pulse. Nanosensors encode different events using different center frequencies with non overlapping half power bandwidth over the entire terahertz band. Using uniform linear array (ULA) antenna, the base station localizes the events by estimating the direction of arrival of the pulse and classifies them from the center frequency estimated by spectral centroid of the received signal. Simulation results confirm that, from a distance of 1 meter, a 6th derivative Gaussian pulse consuming only 1 atto Joule can achieve localization and classification accuracies of 1.58 degree and 98.8%, respectively.
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PDF链接：
https://arxiv.org/pdf/1808.06764