Generalized Spatio Temporal Channel And System Characterization

Generalized Spatio-Temporal Channel and System Characterization

This book presents new research results on channel characterization and modeling. MIMO channel characterization and modeling techniques are investigated. The first part exposes a generalized and systematic representation of systems and channels in the spatio-temporal domains. It is a generalization of the concepts introduced in the research literature: it consists of a set of sixteen kernel functions and eight system functions, in time, frequency, space and wave-vector domains. A series of examples illustrates the concept. In the second part, a space-time signal measurement technique is introduced along with a wave-vector-frequency spectrum estimation method. These are employed to create a large virtual antenna array from a small number of antenna elements. A new calibration technique to estimate measured wave vector spectra is presented. In the last part, a generalized view of the Doppler phenomenon, based on the characterization technique is presented. Here, the Doppler spectra, caused by scatterer mobility under different scatterer velocity distributions, are investigated. Fixed-wireless scenarios, with stationary transmitters and receivers with mobile scatterers are analyzed.

On Modeling the Spatiotemporal Processing Characteristics of the Retina

Advances in Spatio-Temporal Analysis

Developments in Geographic Information Technology have raised the expectations of users. A static map is no longer enough; there is now demand for a dynamic representation. Time is of great importance when operating on real world geographical phenomena, especially when these are dynamic. Researchers in the field of Temporal Geographical Information Systems (TGIS) have been developing methods of incorporating time into geographical information systems. Spatio-temporal analysis embodies spatial modelling, spatio-temporal modelling and spatial reasoning and data mining. Advances in Spatio-Temporal Analysis contributes to the field of spatio-temporal analysis, presenting innovative ideas and examples that reflect current progress and achievements.