Title
A Sub-Nyquist Rate Compressive Sensing Data Acquisition Front-End
Abstract
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.
Year
DOI
Venue
2012
10.1109/JETCAS.2012.2221531
IEEE J. Emerg. Sel. Topics Circuits Syst.
Keywords
Field
DocType
optimisation,cmos integrated circuits,sub-nyquist rate compressive sensing,l1-based optimization algorithm,sub-nyquist adc,pseudorandom number sequence,signal sampling,analogue-digital conversion,random number generation,signal sparsity,wideband front-end,compressive sensing (cs),distortion,analog-to-digital converters (adcs),signal distortion,equivalent sampling rate,low-power circuit,sparse input signal,compressed sensing,complementary metal oxide semiconductor process,frequency 5 mhz to 500 mhz,a priori signal model,size 90 nm,analog-to-digital converter,signal reconstruction,wideband multitone test signal,data acquisition frontend,signal detection,random sequences,generators
Computer science,Sampling (signal processing),Signal-to-noise ratio,Electronic engineering,Analog signal,Distortion,Nyquist rate,Signal transfer function,Signal reconstruction,Compressed sensing
Journal
Volume
Issue
ISSN
2
3
2156-3357
Citations 
PageRank 
References 
5
0.57
0
Authors
7
Name
Order
Citations
PageRank
Xi Chen150.57
Ehab A. Sobhy2182.72
Zhuizhuan Yu314511.51
Sebastian Hoyos423429.24
José Silva-Martínez526739.39
Samuel Palermo614222.07
Brian M. Sadler73179286.72