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

Autor:	Jose Silva-Martinez, Xi Chen, Samuel Palermo, Zhuizhuan Yu, Sebastian Hoyos, Brian M. Sadler, E. A. Sobhy
Rok vydání:	2012
Předmět:	Analog signal Compressed sensing Sampling (signal processing) Computer science Signal reconstruction Distortion Electronic engineering Nyquist rate Electrical and Electronic Engineering Signal transfer function Algorithm Signal
Zdroj:	IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 2:542-551
ISSN:	2156-3365 2156-3357
DOI:	10.1109/jetcas.2012.2221531
Popis:	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 mm2.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::67af88e09b5f79d9e99276941fa5810e https://doi.org/10.1109/jetcas.2012.2221531 Zobrazit plný text záznamu