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Analog compressed sensing for RF propagation channel sounding

机译:模拟压缩感测,用于RF传播通道探测

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Massively broadband® RF channel sounding is severely constrained by the sampling rates required for analog to digital conversion. Analog compressed sensing (CS) techniques based on Xampling have demonstrated the ability to lower sampling rates far below the Nyquist rate. Here, we show attributes of the multipath channel sounding problem appear to be well suited to CS approaches for reducing measurement acquisition time while simultaneously estimating time delays, multipath amplitudes, and angles of arrival. This paper presents results of the fusion of CS with modern channel sounding. We show measured propagation data from 60 GHz field trials and note the channel sparsity in time and space. We then propose an architecture for the first massively broadband CS channel sounder based on the Xampling framework (which we call the Channel Sounding Xampler) to exploit the sparsity, and we use field measurements to explore tradeoffs between analog and digital signal processing to perform channel impulse response (CIR) parameter estimation in real time. We also offer conceptual approaches for the Channel Sounding Xampler designed to trade off analog and digital components with the goal of improving CIR acquisition at sub-THz frequencies.
机译:大规模的宽带®RF通道探测受到模数转换所需的采样率的严重限制。基于Xampling的模拟压缩传感(CS)技术已证明能够将采样率降低到远低于Nyquist率的水平。在这里,我们显示了多径信道探测问题的属性似乎非常适合CS方法,以减少测量获取时间,同时估计时间延迟,多径幅度和到达角度。本文介绍了CS与现代声道探测技术融合的结果。我们显示了从60 GHz现场试验测得的传播数据,并注意到了时间和空间上的信道稀疏性。然后,我们基于Xampling框架(我们称为Channel Sounding Xampler)为第一个大规模宽带CS信道探测仪提出一种架构,以利用稀疏性,并且我们使用现场测量来探索模拟和数字信号处理之间的权衡,以执行信道脉冲实时响应(CIR)参数估计。我们还为Channel Sounding Xampler提供概念方法,旨在权衡模拟和数字组件,以改善在低于THz频率下的CIR采集。

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