InCov: Indoor Coverage Prediction tool for UMTS, HSDPA, WLAN and future wireless data communications systems

Fonte Standard Gras
Identifiant

Unité de recherche

INNOSUISSE

Numéro de projet

9155.1;3 PFES-ES

Titre du projet

InCov: Indoor Coverage Prediction tool for UMTS, HSDPA, WLAN and future wireless data communications systems

Titre du projet anglais

InCov: Indoor Coverage Prediction tool for UMTS, HSDPA, WLAN and future wireless data communications systems

Textes relatifs à ce projet

	Allemand	Français	Italien	Anglais
Description succincte	-	-	-
Résumé des résultats (Abstract)	-	-	-

Textes saisis

Catégorie	Texte
Description succincte (Anglais)	InCov: Indoor Coverage Prediction tool for UMTS, HSDPA, WLAN and future wireless data communications systems
Résumé des résultats (Abstract) (Anglais)	Current coverage prediction tools for indoor environements are not satisfying in terms of usefulness and accuracy. Precious time is waisted to gather the required building data and to compute inaccurate solutions which must be modified by experienced radio planner. An original approach, called PixelFlow, is proposed to develop a profitable and attractive planning tool for indoor radio network planning projects. The PixelFlow approach has a unique potential since it can provide sufficiently accurate results despite approximate building layouts and data. This will mitigate many disadvantages of current coverage prediction tools. The PixelFlow model from the EIA-FR, enhanced and validated in cooperation with Ericsson Switzerland would foster the competence of the project team. This project will also benefit from additional pratical experiences from experts of the Ericsson Indoor Competence Center in Spain. With such national and international references, the proposed prediction model could become a successful commercial product.

Catégorie

Texte

Description succincte
(Anglais)

InCov: Indoor Coverage Prediction tool for UMTS, HSDPA, WLAN and future wireless data communications systems

Résumé des résultats (Abstract)
(Anglais)

Current coverage prediction tools for indoor environements are not satisfying in terms of usefulness and accuracy. Precious time is waisted to gather the required building data and to compute inaccurate solutions which must be modified by experienced radio planner. An original approach, called PixelFlow, is proposed to develop a profitable and attractive planning tool for indoor radio network planning projects. The PixelFlow approach has a unique potential since it can provide sufficiently accurate results despite approximate building layouts and data. This will mitigate many disadvantages of current coverage prediction tools. The PixelFlow model from the EIA-FR, enhanced and validated in cooperation with Ericsson Switzerland would foster the competence of the project team. This project will also benefit from additional pratical experiences from experts of the Ericsson Indoor Competence Center in Spain. With such national and international references, the proposed prediction model could become a successful commercial product.