A passive and low-complexity Compressed Sensing architecture based on a charge-redistribution SAR ADC

An innovative analog-to-digital converter (ADC) architecture is proposed, with the aim of acquiring an input signal according to the Compressed Sensing (CS) paradigm and without the need for dedicated active analog blocks. Its core is the capacitive array employed in traditional successive-approxima...

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Bibliographic Details
Published in:Integration (Amsterdam) 2020-11, Vol.75, p.40-51
Main Authors: Paolino, Carmine, Prono, Luciano, Pareschi, Fabio, Mangia, Mauro, Rovatti, Riccardo, Setti, Gianluca
Format: Article
Language:English
Subjects:
Algorithms
Analog
Analog to digital conversion
Analog to digital converters
Architecture
Arrays
Circuit design
Circuits
Compressed sensing
Decoding
Deep neural networks
Electrocardiography
Leakage
Leakage compensation
Leakage current
Neural networks
Sensors
Signal processing
Signal reconstruction
Sub-Nyquist sampling
Successive approximation register
Switches
Citations: Items that this one cites
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Description
Summary:An innovative analog-to-digital converter (ADC) architecture is proposed, with the aim of acquiring an input signal according to the Compressed Sensing (CS) paradigm and without the need for dedicated active analog blocks. Its core is the capacitive array employed in traditional successive-approximation-register (SAR) ADCs. Introducing only a few additional switches, the array can compute the linear combination of consecutive signal samples, as required by the CS encoding. To manage the presence of leakage currents, which may impair signal reconstruction, a compensation circuit is considered, allowing close-to-ideal performance of the system when properly designed. A neural network-based decoding strategy is also analyzed, with up to 20 dB of additional reconstruction quality with respect to standard algorithms. Synthetic electrocardiogram signals are used to validate optimizations both at the hardware level in the encoding block and at the software level in the decoder. •A novel analog-to-digital converter compatible with Compressed Sensing is proposed.•Avoiding the use of active analog blocks, the potential saving in energy is remarkable.•Degradation induced by leakage currents is countered by a compensation circuit.•A deep neural network-based decoder can be used to achieve performance close to ideal.
ISSN:0167-9260
1872-7522
DOI:10.1016/j.vlsi.2020.05.007