Description
Springer Linear Estimation And Detection In Krylov Subspaces 2007 Edition by Guido K. E. Dietl
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. Table of contents : 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.