Compressed-and-forward: Compressive sensing for cooperative communication

Chia Hung Yeh*, Yu Liang Lin, Cheng Chih Liu, Wan Jen Huang

*Corresponding author for this work

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

Abstract

Cooperative communication has been shown that it is an effective way to achieve spatial diversity in order to combat the user-outage caused by effects fading channel. Except for amplify-and-forward (AF) and decode-and-forward (DF), compressed-and-forward (CF) is also an efficient forwarding strategy. In the existing CF protocol, the relay will switch to the DF mode when the source transmitted signal can be recovered by the relay completely; however, no further compression is made in this scheme. This paper proposes a new CF scheme. The relay will estimate if the codeword in a predefined block can be succeeded decoded, then choose the corresponding forwarding methods which are based on joint source-channel coding or compressive sensing. At the decode side, a joint decoder is designed to decode the source according to the relay compression mode. Simulation results show that the proposed CF scheme can acquire the spatial diversity and outperform AF and DF schemes.

Original languageEnglish
Title of host publicationISPACS 2012 - IEEE International Symposium on Intelligent Signal Processing and Communications Systems
Pages319-322
Number of pages4
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event20th IEEE International Symposium on Intelligent Signal Processing and Communications Systems, ISPACS 2012 - Tamsui, New Taipei City, Taiwan
Duration: 2012 Nov 42012 Nov 7

Publication series

NameISPACS 2012 - IEEE International Symposium on Intelligent Signal Processing and Communications Systems

Other

Other20th IEEE International Symposium on Intelligent Signal Processing and Communications Systems, ISPACS 2012
Country/TerritoryTaiwan
CityTamsui, New Taipei City
Period2012/11/042012/11/07

Keywords

  • compressed-and-forward
  • compressive sensing
  • cooperative communication
  • joint source-channel coding

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Signal Processing

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