Channel estimation for time-varying MIMO relay systems

Chiong, Choo W. R., Rong, Yue and Xiang, Yong 2015, Channel estimation for time-varying MIMO relay systems, IEEE transactions on wireless communications, vol. 14, no. 12, pp. 6752-6762, doi: 10.1109/TWC.2015.2459700.

Attached Files
Name Description MIMEType Size Downloads

Title Channel estimation for time-varying MIMO relay systems
Author(s) Chiong, Choo W. R.
Rong, Yue
Xiang, YongORCID iD for Xiang, Yong
Journal name IEEE transactions on wireless communications
Volume number 14
Issue number 12
Start page 6752
End page 6762
Total pages 11
Publisher IEEE
Place of publication Piscataway, N.J.
Publication date 2015-12-01
ISSN 1536-1276
Keyword(s) Science & Technology
Engineering, Electrical & Electronic
Channel estimation
MIMO relay
superimposed training
time-varying channel
Summary In this paper, we investigate the channel estimation problem for multiple-input multiple-output (MIMO) relay communication systems with time-varying channels. The time-varying characteristic of the channels is described by the complex-exponential basis expansion model (CE-BEM). We propose a superimposed channel training algorithm to estimate the individual first-hop and second-hop time-varying channel matrices for MIMO relay systems. In particular, the estimation of the second-hop time-varying channel matrix is performed by exploiting the superimposed training sequence at the relay node, while the first-hop time-varying channel matrix is estimated through the source node training sequence and the estimated second-hop channel. To improve the performance of channel estimation, we derive the optimal structure of the source and relay training sequences that minimize the mean-squared error (MSE) of channel estimation. We also optimize the relay amplification factor that governs the power allocation between the source and relay training sequences. Numerical simulations demonstrate that the proposed superimposed channel training algorithm for MIMO relay systems with time-varying channels outperforms the conventional two-stage channel estimation scheme.
Language eng
DOI 10.1109/TWC.2015.2459700
Field of Research 080199 Artificial Intelligence and Image Processing not elsewhere classified
0906 Electrical And Electronic Engineering
1005 Communications Technologies
0805 Distributed Computing
Socio Economic Objective 890103 Mobile Data Networks and Services
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2015, IEEE
Persistent URL

Connect to link resolver
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 9 times in TR Web of Science
Scopus Citation Count Cited 13 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 287 Abstract Views, 3 File Downloads  -  Detailed Statistics
Created: Wed, 20 Jan 2016, 10:37:44 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact