Decentralized joint sparsity pattern recovery using 1-bit compressive sensing

Swatantra Kafle, Bhavya Kailkhura, Thakshila Wimalajeewa, Pramod Kumar Varshney

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

3 Scopus citations

Abstract

We address the problem of decentralized joint sparsity pattern recovery based on 1-bit compressive measurements in a distributed network. We assume that the distributed nodes observe sparse signals which share the same but unknown sparsity pattern. Each node obtains measurements via random projections and further quantizes its measurement vector element-wise to 1-bit. We develop two decentralized variants of the binary iterative hard thresholding (BIHT) algorithm where each node communicates only with its one hop neighbors and exchanges its measurement information. This stage is followed by index fusion stage. For first and second algorithms, index fusion is performed at the end of and during BIHT iterations, respectively. The global estimate of the support set in both the algorithms is obtained by fusing all the final local estimates. Experimental results show that the proposed collaborative algorithms have better (or at least similar) performance compared to the centralized version.

Original languageEnglish (US)
Title of host publication2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1354-1358
Number of pages5
ISBN (Electronic)9781509045457
DOIs
StatePublished - Apr 19 2017
Event2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Washington, United States
Duration: Dec 7 2016Dec 9 2016

Other

Other2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016
CountryUnited States
CityWashington
Period12/7/1612/9/16

Keywords

  • 1-bit compressive sensing
  • Binary iterative hard thresholding (BIHT)
  • Compressive sensing
  • Information fusion
  • Sparsity pattern recovery

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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  • Cite this

    Kafle, S., Kailkhura, B., Wimalajeewa, T., & Varshney, P. K. (2017). Decentralized joint sparsity pattern recovery using 1-bit compressive sensing. In 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings (pp. 1354-1358). [7906062] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobalSIP.2016.7906062