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Robust Signal Processing for Wireless Communications / by Frank A. Dietrich.

Por: Colaborador(es): Tipo de material: TextoTextoSeries Foundations in Signal Processing, Communications and Networking ; 2Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008Descripción: xi, 280 p recurso en líneaTipo de contenido:
  • texto
Tipo de medio:
  • computadora
Tipo de portador:
  • recurso en línea
ISBN:
  • 9783540742494
Formatos físicos adicionales: Edición impresa:: Sin títuloClasificación LoC:
  • TK1-9971
Recursos en línea:
Contenidos:
Channel Estimation and Prediction -- Estimation of Channel and Noise Covariance Matrices -- Linear Precoding with Partial Channel State Information -- Nonlinear Precoding with Partial Channel State Information.
Resumen: This book treats the robust design of signal processing algorithms for wireless communications which are based on an incomplete model of the propagation channel. The systematic treatment of this practical problem focuses on signal processing tasks in the physical layer with multiple antennas and relies on a description of the errors and uncertainties in the system's model. It applies principles of modern estimation, optimization, and information theory. Tutorial introductions to relevant literature and mathematical foundations provide the necessary background and context to the reader. The book contains detailed derivations and enlightening insights covering the following topics in detail: Training-based multiple-input multiple-output (MIMO) channel estimation Robust minimax estimation of the wireless communication channel Robust minimax prediction of the wireless communication channel based on the maximum Doppler frequency Identification of channel and noise correlations (power delay profile, spatial and temporal correlations, spatial correlations of interference) Interpolation of band-limited autocovariance sequences Robust linear and nonlinear precoding for the multi-user downlink with multiple antennas, which is based on incomplete channel state information or channel correlations (performance measures, duality, robust Tomlinson-Harashima precoding, nonlinear beamforming)
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Springer eBooks

Channel Estimation and Prediction -- Estimation of Channel and Noise Covariance Matrices -- Linear Precoding with Partial Channel State Information -- Nonlinear Precoding with Partial Channel State Information.

This book treats the robust design of signal processing algorithms for wireless communications which are based on an incomplete model of the propagation channel. The systematic treatment of this practical problem focuses on signal processing tasks in the physical layer with multiple antennas and relies on a description of the errors and uncertainties in the system's model. It applies principles of modern estimation, optimization, and information theory. Tutorial introductions to relevant literature and mathematical foundations provide the necessary background and context to the reader. The book contains detailed derivations and enlightening insights covering the following topics in detail: Training-based multiple-input multiple-output (MIMO) channel estimation Robust minimax estimation of the wireless communication channel Robust minimax prediction of the wireless communication channel based on the maximum Doppler frequency Identification of channel and noise correlations (power delay profile, spatial and temporal correlations, spatial correlations of interference) Interpolation of band-limited autocovariance sequences Robust linear and nonlinear precoding for the multi-user downlink with multiple antennas, which is based on incomplete channel state information or channel correlations (performance measures, duality, robust Tomlinson-Harashima precoding, nonlinear beamforming)

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