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Bibliographic record number: 638826

Journal

Authors: Horvat, Goran; Rimac-Drlje, Snježana; Žagar, Drago
Title: Fade Depth Prediction Using Human Presence for Real Life WSN Deployment
( Fade Depth Prediction Using Human Presence for Real Life WSN Deployment )
Source: Radioengineering (1210-2512) 22 (2013), 3; 758-768
Paper type: article
Keywords: Fade depth prediction; human presence; human density; received strength signal indicator; wireless sensor net-works; ZigBee.
( Fade depth prediction; human presence; human density; received strength signal indicator; wireless sensor net-works; ZigBee. )
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.
Project / theme: 165-0362027-1479, 165-0361630-1636
Original language: eng
Citation databases: Scopus
SCI-EXP, SSCI i/ili A&HCI
Science Citation Index Expanded (SCI-EXP) (sastavni dio Web of Science Core Collectiona)
Category: Znanstveni
Research fields:
Electrical engineering
URL: http://www.radioeng.cz/fulltexts/2013/13_03_0758_0768.pdf
URL cjelovitog rada:
Google Scholar: Fade Depth Prediction Using Human Presence for Real Life WSN Deployment
Contrib. to CROSBI by: Goran Horvat (goran.horvat@etfos.hr), 1. Kol. 2013. u 20:37 sati



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