Robust Multiple Input Output Communications
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Robust Multiple-Input-Output Communications
Multiple antennas at both the transmitter and receiver is known output (MIMO) as multiple-input multiple-system. This has emerged as the most promising technique for improving the performance of wireless digital transmission systems as well as allowing higher data rates to be obtained for a given bandwidth. A consequence of the MIMO wireless communications revolution is that multipath scattering of the transmitted signal has moved from being a problem to being a valuable resource. This has happened to such extent that MIMO systems have come to rely on this resource. However, away from dense urban and indoor environments such as Australian rural and remote areas with wide open spaces and flat or smooth undulating terrain such rich scattering can be hard to find. This research seeks to develop MIMO schemes which will give robust and reliable performance in environments that can change rapidly from rich scattering environment to clear line of sight between transmitter and receiver. Wirelesss communications system which are robust to changing environment conditions are a particular important factor in military communication systems as well as for civilian emergency services. In this work, polarization is proposed as a source of diversity in wireless communications. Polarization diversity is particularly suited to the Australian rural and remote environment where wide open spaces and flat or smooth undulating terrain give rise to line of sight conditions between the transmitter and the receiver. The polarization diversity of transmitted signals is mostly preserved by the line-of-sight environment presenting an opportunity for transmitter and receiver diversity techniques, Another aspect of the research presented here is the development of fast, fixed complexity, decoding algorithms for space-time codes that are robust to the changing transmission conditions. Reliable high rate transmission over the MIMO system ca only be achieved through "space-time coding."
Proceedings of the International Conference on Data Engineering and Communication Technology
This two-volume book contains research work presented at the First International Conference on Data Engineering and Communication Technology (ICDECT) held during March 10–11, 2016 at Lavasa, Pune, Maharashtra, India. The book discusses recent research technologies and applications in the field of Computer Science, Electrical and Electronics Engineering. The aim of the Proceedings is to provide cutting-edge developments taking place in the field data engineering and communication technologies which will assist the researchers and practitioners from both academia as well as industry to advance their field of study.
Robust Signal Processing for Wireless Communications
Author: Frank Dietrich
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-10-25
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 for signal processing in the physical layer with multiple antennas. The design of robust signal processing algorithms is based on a description of the errors and the uncertainties in the system's model. It applies principles of modern estimation, optimization, and information theory. Tutorial introductions to relevant literature and mathematical foundations give the necessary background and context to the reader. The book provides detailed derivations and enlightening insights into the related technical problems covering the following topics in detail: An overview of the principles of 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, robust vector precoding, nonlinear beamforming).