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Linear Estimation and Detection in Krylov Subspaces
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Linear Estimation and Detection in Krylov Subspaces

 Previously published in hardcover
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ISBN-13:
9783642088032
Einband:
Previously published in hardcover
Erscheinungsdatum:
22.11.2010
Seiten:
256
Autor:
Guido K. E. Dietl
Gewicht:
384 g
Format:
237x159x17 mm
Sprache:
Englisch
Beschreibung:

This book focuses on the foundations of linear estimation theory which is essential for effective signal processing. In its first part, it gives a comprehensive overview of several key methods like reduced-rank signal processing and Krylov subspace methods of numerical mathematics. Based on the derivation of the multistage Wiener filter in its most general form, the relationship between statistical signal processing and numerical mathematics is presented. In the second part, the theory is applied to iterative multiuser detection receivers (Turbo equalization) which are typically desired in wireless communication systems. The investigations include exact computational complexity considerations and performance analysis based on extrinsic information transfer charts as well as MonteCarlo simulations.
Theory: Linear Estimation in Krylov Subspaces.- Efficient Matrix Wiener Filter Implementations.- Block Krylov Methods.- Reduced-Rank Matrix Wiener Filters in Krylov Subspaces.- Application: Iterative Multiuser Detection.- System Model for Iterative Multiuser Detection.- System Performance.- Conclusions.
This book focuses linear estimation theory, which is essential for effective signal processing. The first section offers a comprehensive overview of key methods like reduced-rank signal processing and Krylov subspace methods of numerical mathematics. Also, the relationship between statistical signal processing and numerical mathematics is presented. In the second part, the theory is applied to iterative multiuser detection receivers (Turbo equalization) which are typically desired in wireless communications systems. This book focuses on the foundations of linear estimation theory which is essential for effective signal processing. In its first part, it gives a comprehensive overview of several key methods like reduced-rank signal processing and Krylov subspace methods of numerical mathematics. Based on the derivation of the multistage Wiener filter in its most general form, the relationship between statistical signal processing and numerical mathematics is presented.In the second part, the theory is applied to iterative multiuser detection receivers (Turbo equalization) which are typically desired in wireless communication systems.The investigations include
-exact computational complexity considerations and
- performance analysis based on extrinsic information transfer charts as well as Monte-Carlo simulations.

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