Measurements clustering for robustness improvement of indoor WLAN propagation models

Rida Tahri (1) , Valery Guillet (1) , Patrice Pajusco (1, 2)

1 FTR&D - France Télécom Recherche et Développement [Lannion]
2 MO - Département Micro-Ondes

For indoor Wireless Local Area Networks (WLANs) planning, an accurate propagation modelling is required. Semi-empirical models represent an efficient approach to the indoor channel coverage prediction. Their parameters are estimated from measurement results. In the case called ill-conditioned, the Least Square (LS) regression leads to a bad estimation of the model parameters and thus to numerical instability. In this paper, we present an approach based on the K-means clustering method which allows us to increase the estimation stability. Clustering is used to select tuning points for having a robust estimation.

Domaines: Electronique

Rida Tahri, Valery Guillet, Patrice Pajusco. Measurements clustering for robustness improvement of indoor WLAN propagation models. EW 2007 : 13th European Wireless Conference, Apr 2007, Paris, France. pp.1 - 5. ⟨hal-02316351⟩