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首页> 外文期刊>Signal Processing, IEEE Transactions on >The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding versus Dynamic Range
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The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding versus Dynamic Range

机译:宽带信号采集压缩感知的优缺点:噪声折叠与动态范围

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摘要

Compressive sensing (CS) exploits the sparsity present in many signals to reduce the number of measurements needed for digital acquisition. With this reduction would come, in theory, commensurate reductions in the size, weight, power consumption, and/or monetary cost of both signal sensors and any associated communication links. This paper examines the use of CS in the design of a wideband radio receiver in a noisy environment. We formulate the problem statement for such a receiver and establish a reasonable set of requirements that a receiver should meet to be practically useful. We then evaluate the performance of a CS-based receiver in two ways: via a theoretical analysis of its expected performance, with a particular emphasis on noise and dynamic range, and via simulations that compare the CS receiver against the performance expected from a conventional implementation. On the one hand, we show that CS-based systems that aim to reduce the number of acquired measurements are somewhat sensitive to signal noise, exhibiting a 3 dB SNR loss per octave of subsampling, which parallels the classic noise-folding phenomenon. On the other hand, we demonstrate that since they sample at a lower rate, CS-based systems can potentially attain a significantly larger dynamic range. Hence, we conclude that while a CS-based system has inherent limitations that do impose some restrictions on its potential applications, it also has attributes that make it highly desirable in a number of important practical settings.
机译:压缩感测(CS)利用许多信号中存在的稀疏性来减少数字采集所需的测量次数。理论上,随着这种减少,信号传感器和任何相关的通信链路的尺寸,重量,功耗和/或金钱成本将相应减少。本文考察了在嘈杂环境中宽带无线电接收机设计中CS的使用。我们为此类接收方制定问题陈述,并建立一组合理的要求,接收方应满足这些要求以实用。然后,我们通过两种方式评估基于CS的接收机的性能:通过对其预期性能的理论分析,尤其是噪声和动态范围,以及通过将CS接收机与常规实现的预期性能进行比较的模拟。一方面,我们表明,旨在减少获取的测量次数的基于CS的系统对信号噪声有些敏感,在二次采样的每倍频程中表现出3 dB的SNR损失,这与经典的噪声折叠现象相似。另一方面,我们证明由于基于CS的系统采样率较低,因此可以潜在地获得较大的动态范围。因此,我们得出的结论是,尽管基于CS的系统具有固有的局限性,但确实对其潜在的应用施加了一些限制,但它的属性也使其在许多重要的实际环境中都非常受欢迎。

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