Compressive detection of direct sequence spread spectrum signals

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

Compressive detection of direct sequence spread spectrum signals

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Author(s): Feng Liu¹ ; Michael W. Marcellin² ; Nathan A. Goodman³ ; Ali Bilgin⁴
- Affiliations: 1: College of Electronic Information and Optical Engineering , Nankai University , Tianjin , People's Republic of China ;
  2: Department of Electrical and Computer Engineering , University of Arizona , Tucson, AZ , USA ;
  3: School of Electrical and Computer Engineering , University of Oklahoma , Norman, OK , USA ;
  4: Department of Biomedical Engineering and Electrical and Computer Engineering , University of Arizona , Tucson, AZ , USA
Source: Volume 54, Issue 24, 29 November 2018, p. 1379 – 1381
DOI: 10.1049/el.2018.6280 , Print ISSN 0013-5194, Online ISSN 1350-911X

Received 16/07/2018, Published 31/10/2018

In spread spectrum (SS) communications, the input signal is spread over a wider bandwidth to avoid interference or interception. One of the most common SS techniques is direct sequence SS (DSSS). In this Letter, the authors propose non-cooperative compressive detection techniques for DSSS signals. The proposed compressive detection framework allows the use of random as well as designed measurement kernels. A technique for designing compressive measurement kernels which exploit DSSS signal structure and non-uniform usage of spreading codes is proposed. Theoretical and simulation results are provided to compare the performance of the proposed methods with their conventional counterparts.

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