Compressed channel estimation for sparse multipath non-orthogonal amplify-and-forward cooperative networks

Guan Gui, Wei Peng, Abolfazl Mehbodniya, Fumiyuki Adachi

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

6 Citations (Scopus)

Abstract

Coherent detection and demodulation at the receiver requires channel state information (CSI). We investigate channel estimation problem in sparse multipath non-orthogonal amplifyand- forward (NAF) cooperative networks. Traditional linear estimation methods can obtain lower bound at the cost of spectrum efficiency which is becoming more and more scarcity. In this paper, system model is described from sparse representation perspective. Based on the compressed sensing theory, we propose several compressed channel estimation methods to exploit sparsity of the cooperative channels. Simulation results confirm the superiority of proposed methods than LS-based linear estimation method.

Original languageEnglish
Title of host publicationIEEE 75th Vehicular Technology Conference, VTC Spring 2012 - Proceedings
DOIs
Publication statusPublished - 2012 Aug 20
EventIEEE 75th Vehicular Technology Conference, VTC Spring 2012 - Yokohama, Japan
Duration: 2012 May 62012 Jun 9

Publication series

NameIEEE Vehicular Technology Conference
ISSN (Print)1550-2252

Other

OtherIEEE 75th Vehicular Technology Conference, VTC Spring 2012
CountryJapan
CityYokohama
Period12/5/612/6/9

Keywords

  • Compressed channel estimation
  • cooperative networks
  • non-orthogonal amplify-to-forward (NAF)
  • sparse representation

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

Fingerprint Dive into the research topics of 'Compressed channel estimation for sparse multipath non-orthogonal amplify-and-forward cooperative networks'. Together they form a unique fingerprint.

Cite this