Analog compressed sensing for multiband signals with non-modulated Slepian basis

Xianjun Yang, E. Dutkiewicz, Qimei Cui, Xiaojing Huang, Xiaofeng Tao, Gengfa Fang
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引用次数: 1

Abstract

Recently, the recovery performance of analog Compressed Sensing (CS) has been significantly improved by representing multiband signals with the modulated and merged Slepian basis (MM-Slepian dictionary), which avoids the frequency leakage effect of the Discrete Fourier Transform (DFT) basis. However, the MM-Slepian dictionary has a very large scale and corresponds to a large-scale measurement matrix, which leads to high recovery computational complexity. This paper resolves the above problem by modulating and band-limiting the multiband signal rather than modulating the Slepian basis. Specifically, instead of using the MM-Slepian dictionary to represent the whole multiband signal, we propose to use the non-modulated Slepian basis to represent the modulated and band-limited version of the multiband signal based on the recently proposed Modulated Wideband Converter (MWC). Furthermore, based on the analytical derivation with the non-modulated Slepian basis, we propose an Interpolation Recovery (IR) algorithm to take full advantage of the Slepian basis, whereas the Direct Recovery (DR) algorithm using the Moore-Penrose pseudo-inverse cannot achieve this. Simulation results verify that, with low recovery computational load, the non-modulated Slepian basis combined with the IR algorithm improves the recovery SNR by up to 35 dB compared with the DFT basis in noise-free environment.
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非调制睡眠基多频带信号的模拟压缩感知
近年来,利用调制合并的Slepian基(MM-Slepian字典)表示多波段信号,避免了离散傅里叶变换基(DFT)的频率泄漏效应,显著提高了模拟压缩感知(CS)的恢复性能。但是MM-Slepian字典的规模非常大,对应的测量矩阵非常大,导致恢复的计算复杂度很高。本文通过对多波段信号进行调制和限带来解决上述问题,而不是对Slepian基进行调制。具体来说,我们建议使用非调制的Slepian基来表示基于最近提出的调制宽带转换器(MWC)的多带信号的调制和带限制版本,而不是使用MM-Slepian字典来表示整个多带信号。此外,基于非调制Slepian基的解析推导,我们提出了一种插值恢复(IR)算法,以充分利用Slepian基,而使用Moore-Penrose伪逆的直接恢复(DR)算法无法实现这一点。仿真结果表明,在无噪声环境下,与DFT基相比,非调制Slepian基与IR算法相结合的恢复信噪比提高了35 dB,恢复计算量低。
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