Deterministic Approach for Fast Simulations of Indoor Radio Wave Propagation

The multiresolution frequency domain parflow (MR-FDPF) approach is applied to radio wave propagation in indoor environments. This method allows for a better understanding of indoor propagation and hence greatly assists the development of WiFi-like network planning tools. The efficiency of such wirel...

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Veröffentlicht in:IEEE transactions on antennas and propagation 2007-03, Vol.55 (3), p.938-948
Hauptverfasser: Gorce, J.-M., Jaffres-Runser, K., de la Roche, G.
Format: Artikel
Sprache:eng
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Zusammenfassung:The multiresolution frequency domain parflow (MR-FDPF) approach is applied to radio wave propagation in indoor environments. This method allows for a better understanding of indoor propagation and hence greatly assists the development of WiFi-like network planning tools. The efficiency of such wireless design tools is strongly impacted by the quality of the coverage predictions which have to be estimated with a limited computational load. The usual approaches are based either on an empirical modeling relying on measurement campaigns or on geometrical optics leading to ray-tracing. While the former approach suffers from a lack of accuracy, the later one needs to balance accuracy with computational load requirements. The new approach proposed herein is based on a finite difference formalism, i.e., the transmission line matrix (TLM). Once the problem is developed in the frequency domain, the linear system thus obtained is solved in two steps: a pre-processing step which consists of an adaptive MR (multigrid) pre-conditioning and a propagation step. The first step computes a MR data structure represented as a binary tree. In the second step the coverage of a point source is obtained by up-and-down propagating through the binary tree. This approach provides an exact solution for the linear system whilst significantly reducing the computational complexity when compared with the time domain approach
ISSN:0018-926X
1558-2221
DOI:10.1109/TAP.2007.891811