An Affine Projection Algorithm based transceiver filter for MIMO two-way relaying scheme
05 Jul 2011-pp 1-4
TL;DR: In this article, a two-way MIMO relaying scheme where the transceiver filter at the relay station processes the data using a variant of the Affine Projection Algorithm (APA), known as Partial Rank Algorithm(PRA) was presented.
Abstract: This paper presents a MIMO two-way relaying scheme where the transceiver filter at the Relay Station (RS) processes the data using a variant of the Affine Projection Algorithm (APA), known as Partial Rank Algorithm (PRA) The relaying technique used is Amplify and Forward scheme (AF) The modulation technique used at the nodes S 1 and S 2 is Quadrature Phase Shift Keying (QPSK) The performance of PRA algorithm is verified by comparing its Mean-Square error performance (MSE) and Bit Error Rate (BER) with that of a transceiver filter based on Normalized Least Mean Square (NLMS) algorithm The computational complexity of the algorithm is also tabulated
Citations
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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 Affine Projection Algorithm base..."
...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
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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
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24 May 2010TL;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 Affine Projection Algorithm base..." refers background in this paper
...H denote the expectation and conjugate transpose [6] respectively....
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Book•
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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
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 Affine Projection Algorithm base..." refers background in this paper
...It is relatively easy to obtain CSI at the RS, e.g., by estimating the channel at the RS in a time division duplex system (TDD) [2]....
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01 Jul 2007
TL;DR: It is shown that the linear MMSE transceive filters are derived which fulfill the zero forcing (ZF) and minimum mean square error (MMSE) criterion, respectively and outperforms the linear ZF transceive filter in terms of overall bit error rate (BER).
Abstract: This paper considers the two-hop relaying case where two nodes S1 and S2 in a wireless network can communicate with each other via an intermediate relay station (RS) which is equipped with multiple antennas and cannot transmit and receive simultaneously on the same channel resources. In oneway relaying, four orthogonal channel resources are required for the transmissions from S1 to S2 and from S2 to S1. MIMO two-way relaying has been introduced as an approach which requires only half the channel resources compared to one-way relaying due to the simultaneous transmission from S1 to S2 and vice versa. For MIMO two-way relaying, a spatial filter matrix is required at the RS which applies both, transmit and receive processing. The design of linear spatial filter matrices, termed transceive filter matrices, is given in this paper. In particular, linear transceive filters are derived which fulfill the zero forcing (ZF) and minimum mean square error (MMSE) criterion, respectively. It is shown that the linear MMSE transceive filter outperforms the linear ZF transceive filter in terms of overall bit error rate (BER). However, for different channel qualities on the two channels to the RS, the choice of the transceive filter influences which direction of communication has a better BER performance.
30 citations
"An Affine Projection Algorithm base..." refers methods in this paper
...I. INTRODUCTION With the advent of MIMO relaying technology the impetus is on developing methods to reduce the computational cost at the transmit (tx) and receive (rx) nodes....
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