A Sub-Nyquist Rate Compressive Sensing Data Acquisition Front-End Academic Article uri icon


  • 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. © 2011 IEEE.

altmetric score

  • 3

author list (cited authors)

  • Chen, X. i., Sobhy, E. A., Yu, Z., Hoyos, S., Silva-Martinez, J., Palermo, S., & Sadler, B. M.

citation count

  • 33

publication date

  • September 2012