DocumentCode
2531959
Title
Big data from the galactic planetary census
Author
Laughlin, Greg
fYear
2012
fDate
24-26 Oct. 2012
Firstpage
7
Lastpage
7
Abstract
Summary form only given. From the earliest beginnings of mobile communications to the present time, there has always been a high demand for realistic mobile radio channel models. This demand is driven by the fact that channel models are indispensable for the performance evaluation, parameter optimisation, and test of mobile communication systems. Channel modelling and simulation techniques are therefore of great importance for electronics and telecommunication engineers who are involved in the development of present and future mobile communication systems. This presentation will start with a review of the basic principles of mobile radio channel modelling and gradually moves to more advanced modelling and simulation techniques. The objective is to provide an overview on commonly used design methodologies enabling the development of channel models for present and future wireless communication systems. All presented channel models have in common that they are derived from a superposition of a finite number of complex sinusoids. However, the design methodologies differ in the way of computing the model parameters determining the statistical behaviour of the channel model. It will be shown that the proposed channel models are widely flexible, which enables an excellent fitting of their principal statistical properties against measurement data of real-world channels or against the statistics of specified reference channel models. Special interest will be paid to the presentation of cutting-edge research on the modelling of mobile-to-mobile MIMO channels, vehicle-to-vehicle MIMO channels, and mobile channels for relay-based cooperative networks. In addition, techniques will be presented for the development of measurement-based mobile radio channel models. The statistical properties of the channel models will be investigated with emphasis on the dis
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Data Understanding (CIDU), 2012 Conference on
Conference_Location
Boulder, CO
Print_ISBN
978-1-4673-4625-2
Type
conf
DOI
10.1109/CIDU.2012.6382184
Filename
6382184
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