Compressive sensing of direct sequence spread spectrum signals

Feng Liu, Michael W. Marcellin, Nathan A. Goodman, Ali Bilgin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


In this paper, Compressive Sensing (CS) methods for Direct Sequence Spread Spectrum (DSSS) signals are introduced. DSSS signals are formed by modulating the original signal by a Pseudo-Noise sequence. This modulation spreads the spectra over a large bandwidth and makes interception of DSSS signals challenging. Interception of DSSS signals using traditional methods require Analog-to-Digital Converters sampling at very high rates to capture the full bandwidth. In this work, we propose CS methods that can intercept DSSS signals from compressive measurements. The proposed methods are evaluated with DSSS signals generated using Maximum-length Sequences and Binary Phase-Shift-Keying modulation at varying signal-to-noise and compression ratios.

Original languageEnglish (US)
Title of host publicationCompressive Sensing III
EditorsFauzia Ahmad
ISBN (Electronic)9781628410464
StatePublished - 2014
EventCompressive Sensing III - Baltimore, United States
Duration: May 7 2014May 9 2014

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


OtherCompressive Sensing III
Country/TerritoryUnited States


  • Compressive Matched Filtering
  • Compressive Sensing
  • DSSS
  • Sensing Matrix Design

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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