Statistical Modeling of Scenario-based indoor WBAN Channels - Télécom Paris
Journal Articles IEEE Transactions on Antennas and Propagation Year : 2024

Statistical Modeling of Scenario-based indoor WBAN Channels

Abstract

This article presents a parametric statistical path loss model for Wireless Body Area Network (WBAN) communications in the context of a scenario based approach for indoor environments. One of the specificities of WBANs is their numerous sources of variability (subject motion and morphology, antennas, local environment, etc.). We focus here on the influence of the environment, in the case of empty rooms. The model, developed for the first ultra wide band (UWB) sub-band (B = [3.1, 4.8] GHz), takes into account the sizes of the rooms (assumed to be parallelepipedic and empty) and the wall characteristics (via an average reflectivity coefficient). They also involve an elaborate categorization of environments. The following methodology was implemented, in order to avoid time-consuming and complex experimental campaigns while still having a relatively representative and sufficient number of statistical samples: firstly, a simplified ray tracing code enabled a large number of different rooms to be sampled at moderate computational cost; secondly, part of these simulations was supported by anechoic chamber measurements; and thirdly, the simulations were carried out using elaborate experimental designs, based on a categorization of environments and a fairly comprehensive study of building industry data. The parametric path loss models obtained significantly reduce their variance.
Fichier principal
Vignette du fichier
Statistical_Modeling_of_Scenario-based_indoor_WBAN_Channels_Accepted.pdf (2.15 Mo) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-04644937 , version 1 (11-07-2024)

Licence

Identifiers

Cite

Badre Youssef, Christophe Roblin, Alain Sibille. Statistical Modeling of Scenario-based indoor WBAN Channels. IEEE Transactions on Antennas and Propagation, 2024, 72 (8), pp.6549-6560. ⟨10.1109/TAP.2024.3421369⟩. ⟨hal-04644937⟩
158 View
13 Download

Altmetric

Share

More