Generalized Approximate Message Passing for Noisy 1-Bit Compressed Sensing with Side-Information

Swatantra Kafle, Thakshila Wimalajeewa, Pramod Kumar Varshney

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

Abstract

We consider the problem of sparse signal reconstruction from noisy 1-bit compressed measurements when the receiver has access to side information. We assume that compressed measurements are corrupted by additive white Gaussian noise before quantization and sign-flip error after quantization. A generalized approximate message passing-based algorithm for signal reconstruction from noisy 1-bit compressed measurements is proposed and then, it is extended to the case when side information is available. We show that 1-bit compressed measurements based signal reconstruction is quite sensitive to noise and the reconstruction performance can be greatly improved by exploiting available side information at the receiver.

Original languageEnglish (US)
Title of host publicationConference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages1964-1968
Number of pages5
ISBN (Electronic)9781538692189
DOIs
StatePublished - Feb 19 2019
Event52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018 - Pacific Grove, United States
Duration: Oct 28 2018Oct 31 2018

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2018-October
ISSN (Print)1058-6393

Conference

Conference52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
CountryUnited States
CityPacific Grove
Period10/28/1810/31/18

Keywords

  • 1-bit compressed measurements
  • approximate message passing
  • side information
  • sparse signal reconstruction

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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  • Cite this

    Kafle, S., Wimalajeewa, T., & Varshney, P. K. (2019). Generalized Approximate Message Passing for Noisy 1-Bit Compressed Sensing with Side-Information. In M. B. Matthews (Ed.), Conference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018 (pp. 1964-1968). [8645169] (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2018-October). IEEE Computer Society. https://doi.org/10.1109/ACSSC.2018.8645169