Sparse channel estimation for OFDM transmission over two-way works

Peng Cheng*, Lin Gui, Meixia Tao, Y. Jay Guo, Xiaojing Huang, Yun Rui

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

7 Citations (Scopus)

Abstract

Compressed sensing (CS) has recently emerged as a powerful signal acquisition paradigm. CS enables the recovery of high-dimensional sparse signals from much fewer samples than usually required. Further, quite a few recent channel measurement experiments show that many wireless channels also tend to exhibit sparsity. In this case, CS theory can be applicable to sparse channel estimation and its effectiveness has been validated in point-to-point (P2P) communication. In this work, we study sparse channel estimation for two-way relay networks (TWRN). Unlike P2P systems, applying CS theory to sparse channel estimation in TWRN is much more challenging. One issue is that the equivalent channels (terminal-relay-terminal) may be no longer sparse due to the linear convolutional operation. On this basis, novel schemes are proposed to solve this problem and effectively improve the accuracy of TWRN channel estimation when using CS theory. Extensive numerical results are provided to corroborate the proposed studies.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Communications, ICC 2012
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages3948-3953
Number of pages6
ISBN (Print)9781457720529
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 IEEE International Conference on Communications, ICC 2012 - Ottawa, ON, Canada
Duration: 10 Jun 201215 Jun 2012

Other

Other2012 IEEE International Conference on Communications, ICC 2012
CountryCanada
CityOttawa, ON
Period10/06/1215/06/12

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