On the feasibility of hardware implementation of sub-Nyquist random-sampling based analog-to-information conversion

In this paper, we successfully demonstrate the feasibility of hardware implementation of a sub-Nyquist random- sampling based analog to information converter (RS-AIC). The RS-AIC is based on the theory of information recovery from random samples using an efficient information recovery algorithm to compute the spectrogram of the signal. Our RS-AIC enables sub-Nyquist acquisition and processing of wideband signals that are sparse in a local Fourier representation. Results from our RS-AIC hardware implementation demonstrate successful reconstruction of signals that are sampled at half the Nyquist-rate while maintaining up to a 51 dB signal-to-noise ratio (SNR), which is equivalent to an 8.5 bit resolution analog to digital converter.