Optimization of adaptive signal processing algorithms for wireless communications is based on a model of the underlying propagation channel. In practice, this model is never known perfectly. For example, its parameters have to be estimated and are only known with significant errors. In this book, a systematic treatment of this practical design problem is provided.

De la contraportada:

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)