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A Sub-Nyquist Rate Compressive Sensing Data Acquisition Front-End

机译:亚奈奎斯特速率压缩传感数据采集前端

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This paper presents a sub-Nyquist rate data acquisition front-end based on compressive sensing theory. The front-end randomizes a sparse input signal by mixing it with pseudo-random number sequences, followed by analog-to-digital converter sampling at sub-Nyquist rate. The signal is then reconstructed using an L1-based optimization algorithm that exploits the signal sparsity to reconstruct the signal with high fidelity. The reconstruction is based on a priori signal model information, such as a multi-tone frequency-sparse model which matches the input signal frequency support. Wideband multi-tone test signals with 4% sparsity in 5~500 MHz band were used to experimentally verify the front-end performance. Single-tone and multi-tone tests show maximum signal to noise and distortion ratios of 40 dB and 30 dB, respectively, with an equivalent sampling rate of 1 GS/s. The analog front-end was fabricated in a 90 nm complementary metal–oxide–semiconductor process and consumes 55 mW. The front-end core occupies 0.93 ${hbox {mm}}^{2}$.
机译:本文提出了一种基于压缩感知理论的亚奈奎斯特速率数据采集前端。前端通过将稀疏输入信号与伪随机数字序列混合来对其进行随机化处理,然后以亚奈奎斯特速率对模数转换器进行采样。然后,使用基于L1的优化算法来重建信号,该算法利用信号稀疏性来以高保真度重建信号。重建基于先验信号模型信息,例如与输入信号频率支持匹配的多音频稀疏模型。在5〜500 MHz频段中稀疏度为4%的宽带多音测试信号被用于实验验证前端性能。单音和多音测试显示最大信噪比和失真比分别为40 dB和30 dB,等效采样率为1 GS / s。模拟前端采用90 nm互补金属-氧化物-半导体工艺制造,功耗为55 mW。前端核心占用0.93 $ {hbox {mm}} ^ {2} $。

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