摘要翻译：
30-300GHz毫米波（mmWave）频段目前正被追求以应对5G、WiFi和IoT网络不断增长的容量需求。由于频率较高，脉冲无线电(IR)在这个频段比现有的其他低频段更适合定位。除了精确定位外，超宽的带宽还可以在同一应用中同时使用多个中心频率，这为红外mmWave网络中的信息编码开辟了新的途径。本文提出了一种新的mmWave红外框架，它可以同时检测到达方向(DOA)和发射脉冲的中心频率。本文以新兴的石墨烯收发器为基础，在mmWave频段(100-300GHz)的较高频率范围内对所提出的框架进行了性能评估。数值实验表明，该框架能在20米处对0.1μWatt的mmWave脉冲进行1度精度的DOA检测，并能在10米处对3种不同的中心频率进行100%的分类。通过改变系统的脉冲率可以进一步提高这些性能。
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英文标题：
《Direction of Arrival and Center Frequency Estimation for Impulse Radio
  Millimeter Wave Communications》
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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：
  The 30-300GHz millimeter wave (mmWave) band is currently being pursued to combat the rising capacity demands in 5G, WiFi, and IoT networks. Due to the high frequency, impulse radio (IR) in this band is better suited for positioning than other existing low-frequency bands. Besides precision positioning, the exceptionally wide bandwidth also enables concurrent use of multiple center frequencies in the same application, which opens up additional avenues of information encoding in IR mmWave networks. In this paper, we propose a new mmWave IR framework that can simultaneously detect direction of arrival (DOA) as well as the center frequency of the transmitted pulse. Based on the emerging graphene-based transceivers, we evaluate the performance of the proposed framework in the higher frequency region of mmWave band (100-300GHz). Numerical experiments demonstrate that the proposed framework can detect the DOA of a 0.1 $\mu$Watt mmWave pulse within 1 degree of precision at 20 meters, and classify three different center frequencies with 100% accuracy from a distance of 10 meters. These performances could be further improved by trading off the pulse rate of the system.
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PDF链接：
https://arxiv.org/pdf/1808.06765