Fade Depth Prediction Using Human Presence for Real Life WSN Deployment
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Date
2013-09
ORCID
Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
Společnost pro radioelektronické inženýrství
Abstract
Current problem in real life WSN deployment is determining fade depth in indoor propagation scenario for link power budget analysis using (fade margin parameter). Due to the fact that human presence impacts the performance of wireless networks, this paper proposes a statistical approach for shadow fading prediction using various real life parameters. Considered parameters within this paper include statistically mapped human presence and the number of people through time compared to the received signal strength. This paper proposes an empirical model fade depth prediction model derived from a comprehensive set of measured data in indoor propagation scenario. It is shown that the measured fade depth has high correlations with the number of people in non-line-of-sight condition, giving a solid foundation for the fade depth prediction model. In line-of-sight conditions this correlations is significantly lower. By using the proposed model in real life deployment scenarios of WSNs, the data loss and power consumption can be reduced by the means of intelligently planning and designing Wireless Sensor Network.
Description
Citation
Radioengineering. 2013, vol. 22, č. 3, s. 758-768. issn 1210-2512
http://www.radioeng.cz/fulltexts/2013/13_03_0758_0768.pdf
http://www.radioeng.cz/fulltexts/2013/13_03_0758_0768.pdf
Document type
Peer-reviewed
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Published version
Date of access to the full text
Language of document
en