Joint sparsity pattern recovery with 1-bit compressive sensing in sensor networks

Vipul Gupta, Bhavya Kailkhura, Thakshila Wimalajeewa, Sijia Liu, Pramod Kumar Varshney

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

4 Scopus citations

Abstract

We study the problem of joint sparsity pattern recovery with 1-bit compressive measurements in a sensor network. Sensors are assumed to observe sparse signals having the same but unknown sparsity pattern. Each sensor quantizes its measurement vector element-wise to 1-bit and transmits the quantized observations to a fusion center. We develop a computationally tractable support recovery algorithm which minimizes a cost function defined in terms of the likelihood function and the ℓ1,∞ norm. We observe that even with noisy 1-bit measurements, joint sparsity pattern can be recovered accurately with multiple sensors each collecting only a small number of measurements.

Original languageEnglish (US)
Title of host publicationConference Record - Asilomar Conference on Signals, Systems and Computers
PublisherIEEE Computer Society
Pages1472-1476
Number of pages5
Volume2016-February
ISBN (Print)9781467385763
DOIs
StatePublished - Feb 26 2016
Event49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States
Duration: Nov 8 2015Nov 11 2015

Other

Other49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
CountryUnited States
CityPacific Grove
Period11/8/1511/11/15

Keywords

  • Compressed sensing
  • maximum-likelihood estimation
  • quantization
  • support recovery

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing

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  • Cite this

    Gupta, V., Kailkhura, B., Wimalajeewa, T., Liu, S., & Varshney, P. K. (2016). Joint sparsity pattern recovery with 1-bit compressive sensing in sensor networks. In Conference Record - Asilomar Conference on Signals, Systems and Computers (Vol. 2016-February, pp. 1472-1476). [7421389] IEEE Computer Society. https://doi.org/10.1109/ACSSC.2015.7421389