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Proceedings ArticleDOI

An IQR-RLS based transceiver filter For MIMO two-way relaying in frequency selective environment

TL;DR: In this article, a two-way relaying scheme where the transceiver filter at the relay station processes the data using Recursive Least Square (RLS) technique based on Inverse QR (IQR) algorithm is presented.
Abstract: This paper presents a MIMO two-way relaying scheme where the transceiver filter at the Relay Station (RS) processes the data using Recursive Least Square (RLS) technique based on Inverse QR (IQR) algorithm. The relaying technique used is Amplify and Forward scheme (AF). The channel is assumed to be frequency selective and the Channel State Information (CSI) is available only at the RS. So the transmit and receive processing are both done at the RS. Orthogonal Frequency Division Multiplexing (OFDM) is used so as to combat the Inter-Symbol Interference (ISI) occurring due to the frequency selectivity of the channel. The performance of the IQR-RLS algorithm is verified by comparing its Mean-Square error performance (MSE) with that of a transceiver filter based on Normalized Least Mean Square (NLMS) algorithm.
Citations
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Proceedings ArticleDOI
29 Aug 2013
TL;DR: A joint adaptive channel estimation and transceiver design scheme for MIMO two-way relay systems in order to reduce the computational complexity at the transmitting nodes and the transceiver is implemented at the relay station.
Abstract: This paper discusses a joint adaptive channel estimation and transceiver design scheme for MIMO two-way relay systems. In order to reduce the computational complexity at the transmitting nodes, the transceiver is implemented at the relay station. Adaptive transceiver consists of an adaptive post equalizer known as receive filter and an adaptive pre-equalizer known as transmit filter. The design of adaptive pre-equalizer requires the knowledge of Channel State Information (CSI) between nodes and relay station. So a channel tracking adaptive filter should be implemented at the relay. Due to the structure of a two-way relay system, the training signals used to train the receive filter can be used to train the channel tracking filter. Thus the adaptive channel estimator and receive filter work simultaneously. The channel estimate is then used to design the transmit filter. The adaptive filters are implemented using the NLMS algorithm. The performance of the proposed scheme is verified by making use of MATLAB simulations.

Cites background or methods from "An IQR-RLS based transceiver filter..."

  • ...A similar joint channel estimation 978-0-7695-5033-6/13 $26.00 © 2013 IEEE DOI 10.1109/ICACC.2013.82 389 and equalization scheme has been implemented in [18] for underwater applications....

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  • ...In order to improve the convergence rate of the adaptive transceiver in [13], Recursive Least Square(RLS) and Affine Projection Algorithm (APA) based transceiver was designed in [14],[15] respectively....

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References
More filters
Book
01 Mar 2004
TL;DR: In this article, the focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them, and a comprehensive introduction to the subject is given. But the focus of this book is not on the optimization problem itself, but on the problem of finding the appropriate technique to solve it.
Abstract: Convex optimization problems arise frequently in many different fields. A comprehensive introduction to the subject, this book shows in detail how such problems can be solved numerically with great efficiency. The focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. The text contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance, and economics.

33,341 citations

Book
24 May 2010
TL;DR: The author presents Perron-Frobenius theory of nonnegative matrices Index, a theory of matrices that combines linear equations, vector spaces, and matrix algebra with insights into eigenvalues and Eigenvectors.
Abstract: Preface 1. Linear equations 2. Rectangular systems and echelon forms 3. Matrix algebra 4. Vector spaces 5. Norms, inner products, and orthogonality 6. Determinants 7. Eigenvalues and Eigenvectors 8. Perron-Frobenius theory of nonnegative matrices Index.

4,979 citations


"An IQR-RLS based transceiver filter..." refers background in this paper

  • ...the lower triangular matrix with positive diagonal elements obtained while cholesky decomposing [ 8 ] the matrix Σ. The matrix P 1/2 will always be a...

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  • ...+ is Moore-Penrose pseudoinverse [ 8 ] of G’T....

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  • ...expectation and conjugate transpose [ 8 ] respectively....

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Book
14 Apr 2008
TL;DR: Adaptive Filters offers a fresh, focused look at the subject in a manner that will entice students, challenge experts, and appeal to practitioners and instructors.
Abstract: Adaptive Filters Adaptive filtering is a topic of immense practical and theoretical value, having applications in areas ranging from digital and wireless communications to biomedical systems. Now, preserving the style and main features of the earlier award-winning publication, Fundamentals of Adaptive Filtering (2005 Terman Award), the author offers readers and instructors a concentrated, systematic, and up-to-date treatment of the subject in this valuable new book. Adaptive Filters allows readers to gain a gradual and solid introduction to the subject, its applications to a variety of topical problems, existing limitations, and extensions of current theories. The book consists of eleven partseach part containing a series of focused lectures and ending with bibliographic comments, problems, and computer projects with MATLAB solutions available to all readers. Additional features include: Numerous tables, figures, and projects Special focus on geometric constructions, physical intuition, linear-algebraic concepts, and vector notation Background material on random variables, linear algebra, and complex gradients collected in three introductory chapters Complete solutions manual available for instructors MATLAB solutions available for all computer projects Adaptive Filters offers a fresh, focused look at the subject in a manner that will entice students, challenge experts, and appeal to practitioners and instructors.

1,458 citations

Journal ArticleDOI
TL;DR: This article introduces three distributed network scenarios that differ in the amount of cooperation between nodes and presents coherent relaying solutions that offer a distributed spatial multiplexing gain even for single-antenna nodes.
Abstract: In this article we review an important class of wireless cooperation protocols known as amplify-and-forward relaying. One or more low-complexity relay nodes assist the communication between sources and destinations without having to decode the signal. This makes AF relaying transparent to modulation and coding of the source/destination communication protocol. It is therefore a highly flexible technology that also qualifies for application in heterogeneous networks comprising many nodes of different complexity or even standards. Recently, two-way relaying was introduced, which is readily combined with AF relaying. It is a spectrally efficient protocol that allows for bidirectional communication between sources and destinations. In order to investigate the potential of wireless AF relaying, we introduce three distributed network scenarios that differ in the amount of cooperation between nodes. New challenges arise in those networks, and we discuss approaches to overcome them. For the most general case of a completely distributed system, we present coherent relaying solutions that offer a distributed spatial multiplexing gain even for single-antenna nodes. Based on real-world experiments, we validate the feasibility of all schemes in our laboratory.

175 citations


"An IQR-RLS based transceiver filter..." refers background or methods in this paper

  • ...The overall channel matrix is defined as the partitioned matrix H = [ H((1)) | H((2)) ]....

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  • ...] at S1 and X((2)) = [ X1((2)), X2((2)),....

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  • ...The nodes S1 and S2 is assumed to have M (1) and M (2) antennas, respectively....

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  • ...During this phase the data to be transmitted from S1 and S2 is processed using scalar transmit filters defined by matrices Q((1)) and Q((2)) respectively where Q((1)) = q((1))IM and Q((2)) = q((2))IM....

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  • ...The overall data vector is defined as a partitioned vector x = [ x((1)) T | x((2)) T ] with covariance matrix Rx = E{ xx } where E{....

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Book
01 Jan 2009
TL;DR: QR Decomposition An Annotated Bibliography contains references to Adaptive Filters, Conventional and Inverse QRD-RLS Algorithms, and Numerical Stability Properties.
Abstract: QR Decomposition An Annotated Bibliography.- to Adaptive Filters.- Conventional and Inverse QRD-RLS Algorithms.- Fast QRD-RLS Algorithms.- QRD Least-Squares Lattice Algorithms.- Multichannel Fast QRD-RLS Algorithms.- Householder-Based RLS Algorithms.- Numerical Stability Properties.- Finite and Infinite-Precision Properties of QRD-RLS Algorithms.- On Pipelined Implementations of QRD-RLS Adaptive Filters.- Weight Extraction of Fast QRD-RLS Algorithms.- Linear Constrained QRD-Based Algorithm.

63 citations