Semi-Stochastic MIMO Channel Model
Channel knowledge is important for network design, control, and optimization. Depending on the particular task, different levels of details need to be considered. Hence, there is a variety of channel models available including the WINNER MIMO channel model. The WINNER model takes into account geometric components, so-called clusters which are represented as circles in the sketch above. However, this components are following a probability distribution. The idea of our semi-stochastic channel model is to substitute the stochastically generated clusters by cluster properties which are given cause of the real environment. We achieve the cluster information by means of our radio wave propagation tool PIROPA. Overall, this allows for an environment-aware MIMO channel model which is beneficial for tasks as network planning or operation. This approach reduces the necessity of cost and time intensive drive tests and measurement campaigns. However, for calibrating purposes they are still advantageous.
Related publications
- F. Schröder, M. Reyer, R. Mathar, Field Strength Prediction for Environment Aware MIMO Channel Models, Proceedings: 6th European Conference on Antennas and Propagation (EUCAP), Prague, Czech, March 2012.
- X. Xu, M. Reyer, F. Schröder, A. Engels, R. Mathar, A Semi-Stochastic Radio Propagation Model for Wireless MIMO Channels, Proceedings: International Symposium on Wireless Communication 2011, Aachen, Deutschland, November 2011.
Related projects
- Realitätsnahe Feldstärkeprädiktion und Mobilitätsmodelle in der Verkehrstelematik, see Project list
- Kanalmodelle für mobile Kommunikationsnetze der vierten Generation und deren Umsetzung in einer virtuellen Testumgebung, see Project list
- Radio wave propagation
- Network planning
- Self-organizing networks
Related student work
- Master Thesis: Analyse eines semi-stochastischen Modells für MIMO-Mobilfunkkanäle an Hand von Messdaten
- Students assisted in writing C++ and MATLAB code.