Low-power Sensor Interfacing and MEMS for Wireless Sensor Networks

Michaelsen, Jørgen Andreas; Ramstad, J. E.; Wisland, Dag T.; Sorasen, O.

doi:10.5772/38725

Cited by 1 publication

(1 citation statement)

References 37 publications

(40 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, BP algorithms are challenging to implement in hardware and are usually significantly slower when compared to greedy pursuit algorithms [26]- [28]. Greedy pursuit algorithms try to minimize 1 solves for that has the smallest -"norm," where is defined as the number of nonzero elements in . 2 The -norm of a vector is defined as the sum of the absolute values of its elements.…”

Section: Compressive Samplingmentioning

confidence: 99%

A Low-Power Compressive Sampling Time-Based Analog-to-Digital Converter

Yenduri

Rocca

Rao

et al. 2012

IEEE J. Emerg. Sel. Topics Circuits Syst.

View full text Add to dashboard Cite

This paper presents a low-power, time-based, compressive sampling architecture for analog-to-digital conversion. A random pulse-position-modulation (PPM) analog-to-digital conversion (ADC) architecture is proposed. A prototype 9-bit random PPM ADC incorporating a pseudo-random sampling scheme is implemented as proof of concept. This approach leverages the energy efficiency of time-based processing. The use of sampling techniques that exploit signal compressibility leads to further improvements in efficiency. The random PPM (pulse-position-modulation) ADC employs compressive sampling techniques to efficiently sample at sub-Nyquist rates. The sub-sampled signal is recovered using a reconstruction algorithm, which is tailored for practical hardware implementation. We develop a theoretical analysis of the hardware architecture and the reconstruction algorithm. Measurements of a prototype random PPM ADC and simulation, demonstrate this theory. The prototype successfully demonstrates a 90% reduction in sampling rate compared to the Nyquist rate for input signals that are 3% sparse in frequency domain.

show abstract