Semi-Blind Carrier Frequency Offset Estimation and Channel Equalization
This SpringerBrief investigates the performance of semi-blind independent component analysis (ICA) based equalization and carrier frequency offset estimation approaches (CFO) for a number of orthogonal frequency division multiplexing (OFDM) based wireless
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Yufei Jiang Xu Zhu Eng Gee Lim Yi Huang Hai Lin
Semi-Blind Carrier Frequency Offset Estimation and Channel Equalization 123
SpringerBriefs in Electrical and Computer Engineering
More information about this series at http://www.springer.com/series/10059
Yufei Jiang • Xu Zhu • Eng Gee Lim Yi Huang • Hai Lin
Semi-Blind Carrier Frequency Offset Estimation and Channel Equalization
123
Yufei Jiang University of Liverpool Liverpool, Merseyside, UK
Xu Zhu University of Liverpool Liverpool, Merseyside, UK
Eng Gee Lim Xi’an Jiaotong-Liverpool University Suzhou, China
Yi Huang University of Liverpool Liverpool, Merseyside, UK
Hai Lin Osaka Prefecture University Osaka, Japan
ISSN 2191-8112 ISSN 2191-8120 (electronic) SpringerBriefs in Electrical and Computer Engineering ISBN 978-3-319-24982-7 ISBN 978-3-319-24984-1 (eBook) DOI 10.1007/978-3-319-24984-1 Library of Congress Control Number: 2015953666 Springer Cham Heidelberg New York Dordrecht London © The Author(s) 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer International Publishing AG Switzerland is part of Springer Science+Business Media (www. springer.com)
Preface
The technologies of wireless communications have experienced a rapid growth over the past two decades. The demands for high-data-rate services have motivated numerous research activities to be carried out. However, the demands are limited by the very scarce bandwidth resource. Commonly, Channel State Information (CSI) and Carrier Frequency Offset (CFO) estimations are performed by using training signals, which reduce the spectral efficiency further. Therefore, it is very urgent and important to improve the bandwidth usage. Independent Component Analysis (ICA) is an efficient Higher-Order Statistics (HOS)-based blind source separation technique by maximizing non-Gaussianity of the ICA output signals. So far, ICA has been applied to a range of fields, including separation of signals in audio applications or brain i
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