Channel Estimation for Frequency-Selective Two-Way MIMO Relay Systems

Chiong, Choo Wee Raymond; Rong, Yue; Xiang, Y.

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Access Status

Open access

Authors

Chiong, Choo Wee Raymond

Rong, Yue

Xiang, Y.

Date

2014

Type

Conference Paper

Metadata

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Citation

Chiong, C.W.R. and Rong, Y. and Xiang, Y. 2014. Channel Estimation for Frequency-Selective Two-Way MIMO Relay Systems, in S. Hanly (ed), The International Symposium on Information Theory and Its Applications, Oct 26 2014, pp. 630-634. Melbourne, Australia: IEEE.

Source Title

Proceedings of the International Symposium on Information Theory and Its Applications

Source Conference

The International Symposium on Information Theory and Its Applications

Additional URLs

http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6979920

School

Department of Electrical and Computer Engineering

Remarks

Copyright © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

URI

http://hdl.handle.net/20.500.11937/31580

Collection

Curtin Research Publications

Abstract

In this paper, we investigate the channel estimation problem for two-way multiple-input multiple-output (MIMO) relay communication systems in frequency-selective fading environments. We propose a superimposed channel training algorithm to estimate the individual channel state information(CSI) of the first-hop and second-hop links for two-way MIMO relay systems with frequency-selective fading channels. In this algorithm, a relay training sequence is superimposed on the received signals at the relay node to assist the estimation of the second-hop channel matrices. The optimal structure of the source and relay training sequences is derived to minimize the mean-squared error (MSE) of channel estimation. We also derive the optimal power allocation between the source and relay trainingsequences. Numerical examples are shown to demonstrate the performance of the proposed algorithm.