Statistical characterization of the 400 MHz in-body propagation channel in in-door environments

Yang, Y; Fang, G; Dutkiewicz, E; Shen, D

Statistical characterization of the 400 MHz in-body propagation channel in in-door environments

Yang, Y Fang, G Dutkiewicz, E

Shen, D

Permalink

Publication Type:: Conference Proceeding
Citation:: 2012 International Symposium on Communications and Information Technologies, ISCIT 2012, 2012, pp. 48 - 53
Issue Date:: 2012-12-01

Closed Access

	Filename	Description	Size
	702972.pdf	Published version	293.96 kB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Yang, Y	en_US
dc.contributor.author	Fang, G	en_US
dc.contributor.author	Dutkiewicz, E https://orcid.org/0000-0002-4268-9286	en_US
dc.contributor.author	Shen, D	en_US
dc.date.issued	2012-12-01	en_US
dc.identifier.citation	2012 International Symposium on Communications and Information Technologies, ISCIT 2012, 2012, pp. 48 - 53	en_US
dc.identifier.isbn	9781467311571	en_US
dc.identifier.uri	http://hdl.handle.net/10453/119545
dc.description.abstract	Channel modeling is the starting point of effective, efficient body-centric communications. Many efforts [2]-[6] have been made to characterize the on-body area propagation channel in static scenarios at various frequency bands in an anechoic chamber. This paper presents an experimental investigation into the in-body channel in 400 MHz MICS Band. By taking into account the joint effect of human movement and multipath effects, the measurements have been conducted in a populated office at very short distances. The dynamic channel behaviour has been captured and based on the statistical analyses of fading duration, a six-state Semi-markov model that considers both Line of Sight (LOS) and Non Line of Sight (NLOS) cases is proposed. Parameters of the Semi-markov model are estimated from the measured data. The validity of this model is confirmed by comparison of the first order and second order statistics of the proposed model with the measured data. © 2012 IEEE.	en_US
dc.relation.ispartof	2012 International Symposium on Communications and Information Technologies, ISCIT 2012	en_US
dc.relation.isbasedon	10.1109/ISCIT.2012.6380948	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Statistical characterization of the 400 MHz in-body propagation channel in in-door environments	en_US
dc.type	Conference Proceeding
utslib.for	0906 Electrical and Electronic Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US

Abstract:

Channel modeling is the starting point of effective, efficient body-centric communications. Many efforts [2]-[6] have been made to characterize the on-body area propagation channel in static scenarios at various frequency bands in an anechoic chamber. This paper presents an experimental investigation into the in-body channel in 400 MHz MICS Band. By taking into account the joint effect of human movement and multipath effects, the measurements have been conducted in a populated office at very short distances. The dynamic channel behaviour has been captured and based on the statistical analyses of fading duration, a six-state Semi-markov model that considers both Line of Sight (LOS) and Non Line of Sight (NLOS) cases is proposed. Parameters of the Semi-markov model are estimated from the measured data. The validity of this model is confirmed by comparison of the first order and second order statistics of the proposed model with the measured data. © 2012 IEEE.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/119545