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Channel estimation and training sequence design in one-way and two-way relay networks Open Access


Other title
relay networks
channel estimation
training sequence design
Type of item
Degree grantor
University of Alberta
Author or creator
Wang, Gongpu
Supervisor and department
Chintha Tellambura (Electrical and Computer Engineering)
Examining committee member and department
Mike MacGregor, Computing Science
Hong-Chuan Yang, Electrical and Computer Engineering, University of Victoria
Masoud Ardakani, Electrical and Computer Engineering
Hai Jiang, Electrical and Computer Engineering
Department of Electrical and Computer Engineering

Date accepted
Graduation date
Doctor of Philosophy
Degree level
Wireless relay networking is a highly active research field. Several relay standards have been or are being specified for next-generation mobile broadband communication systems. Channel estimates are required by wireless nodes to perform essential tasks such as precoding, beamforming and data detection. Thus this thesis focuses on channel estimation for amplify-and-forward (AF) one-way relay networks (OWRNs) and two-way relay networks (TWRNs). For orthogonal frequency-division multiplexing (OFDM) based TWRNs, joint carrier frequency offset (CFO) and channel estimation is investigated. Two new zero-padding (ZP) and cyclic-prefix (CP) transmission protocols are proposed. Both protocols enable an estimator based on the nullingbased least square (NLS) algorithm and perform identically when the block length is large. A detailed performance analysis is given by proving the unbiasedness of the estimator at high signal-to-noise ratio (SNR) and by deriving the closed-form expression of the mean-square error (MSE). Since the two protocols and corresponding NLS algorithm can only estimate the convoluted channel parameters, a superimposed training strategy is proposed to estimate all the individual channel parameters. Specifically, three different algorithms that require different lengths of trainings are designed for the initial parameter estimation and an iterative algorithm is developed to refine the initial estimation results. For TWRNs operating over time-varying fading environments, channel estimation and training sequence design are investigated. A new complex exponential basis expansion model (CE-BEM) is proposed to represent the mobile-to-mobile time-varying channel. To estimate the parameters of this model, a novel pilot symbol-aided transmission scheme is developed such that a linear approach can estimate the convoluted channels. More essentially, two algorithms are designed to extract the BEM coefficients of the individual channels. The optimal training parameters are derived by minimizing the estimation MSE. For OWRNs operating over doubly-selective channels, estimation algorithms and training sequence design are investigated. The CE-BEM is utilized to approximate the doubly-selective channel. Since direct estimation of the CE-BEM coefficients requires large pilot overhead, an efficient estimator is developed that targets only useful channel parameters that could guarantee effective data detection. The training sequence design that can minimize the estimation MSE is also proposed.
License granted by Gongpu Wang ( on 2011-08-20T05:19:37Z (GMT): Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of the above terms. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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