Sparse channel estimation for MIMO-OFDM amplify-and-forward two-way relay networks

Guan Gui, Abolfazl Mehbodniya, Fumiyuki Adachi

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

4 Citations (Scopus)

Abstract

Accurate channel impulse response (CIR) is required for coherent detection and it also helps to improve the quality of service in next-generation wireless communication systems. Linear channel estimation methods, e.g., least square (LS), have been proposed to estimate the CIR. However, these methods never take advantage of the channel sparsity and they also cause performance loss. In this paper, we propose a sparse channel estimation method for multi-input multi-output orthogonal frequency-division multiplexing (MIMO-OFDM) amplify and forward two-way relay networks (AF-TWRN), to exploit the sparse structure information in the CIR for each user. Sparse channel estimation problem is formulated as compressed sensing (CS) using sparse decomposition theory and the estimation process is implemented by LASSO algorithm. Computer simulation results are given to confirm the superiority of the proposed method over the LS-based channel estimation.

Original languageEnglish
Title of host publication2013 IEEE 78th Vehicular Technology Conference, VTC Fall 2013
DOIs
Publication statusPublished - 2013
Event2013 IEEE 78th Vehicular Technology Conference, VTC Fall 2013 - Las Vegas, NV, United States
Duration: 2013 Sep 22013 Sep 5

Publication series

NameIEEE Vehicular Technology Conference
ISSN (Print)1550-2252

Other

Other2013 IEEE 78th Vehicular Technology Conference, VTC Fall 2013
Country/TerritoryUnited States
CityLas Vegas, NV
Period13/9/213/9/5

Keywords

  • Aftwrn
  • Compressed sensing (CS)
  • MIMO-OFDM
  • Sparse channel estimation

ASJC Scopus subject areas

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

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