Regime change: Bit-depth versus measurement-rate in compressive sensing

Jason N. Laska, Richard G. Baraniuk

Research output: Contribution to journalArticlepeer-review

88 Scopus citations

Abstract

The recently introduced compressive sensing (CS) framework enables digital signal acquisition systems to take advantage of signal structures beyond bandlimitedness. Indeed, the number of CS measurements required for stable reconstruction is closer to the order of the signal complexity than the Nyquist rate. To date, the CS theory has focused on real-valued measurements, but in practice measurements are mapped to bits from a finite alphabet. Moreover, in many potential applications the total number of measurement bits is constrained, which suggests a tradeoff between the number of measurements and the number of bits per measurement. We study this situation in this paper and show that there exist two distinct regimes of operation that correspond to high/low signal-to-noise ratio (SNR). In the measurement compression (MC) regime, a high SNR favors acquiring fewer measurements with more bits per measurement; in the quantization compression (QC) regime, a low SNR favors acquiring more measurements with fewer bits per measurement. A surprise from our analysis and experiments is that in many practical applications it is better to operate in the QC regime, even acquiring as few as 1 bit per measurement.

Original languageEnglish (US)
Article number6184331
Pages (from-to)3496-3505
Number of pages10
JournalIEEE Transactions on Signal Processing
Volume60
Issue number7
DOIs
StatePublished - Jul 2012

Keywords

  • Analog-to-digital conversion
  • compressed sensing
  • quantization

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing

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