RF Propagation and Channel Modeling for UWB Wearable Devices

Kamya YEKEH YAZDANDOOST  Kamran SAYRAFIAN-POUR  Kiyoshi HAMAGUCHI  

Publication
IEICE TRANSACTIONS on Communications   Vol.E94-B   No.5   pp.1126-1134
Publication Date: 2011/05/01
Online ISSN: 1745-1345
DOI: 10.1587/transcom.E94.B.1126
Print ISSN: 0916-8516
Type of Manuscript: INVITED PAPER (Special Section on Antenna and Propagation Technologies Contributing to Diversification of Wireless Technologies)
Category: 
Keyword: 
UWB antenna,  immersive visualization system,  channel model,  body area network,  

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Summary: 
Wireless body area network for sensing and monitoring of vital signs is the one of most rapidly growing wireless communication system and Ultra Wide-Band (UWB) is a favorable technology for wearable medical sensors. The wireless body area networks promise to revolutionize health monitoring. However, designers of such systems face a number of challenging tasks. Efficient transceiver design requires in-depth understanding of the propagation media which in this case is the human body surface. The human body is not an ideal medium for RF wave transmission; it is partially conductive and consists of materials of different dielectric constants, thickness and characteristic impedance. The results of the few measurement experiments in recent publications point to varying conclusions in the derived parameters of the channel model. As obtaining large amount of data for many scenarios and use-cases is difficult for this channel, a detailed simulation platform can be extremely beneficial in highlighting the propagation behavior of the body surface and determining the best scenarios for limited physical measurements. In this paper, an immersive visualization environment is presented, which is used as a scientific instrument that gives us the ability to observe three-dimensional RF propagation from wearable medical sensors around a human body. We have used this virtual environment to further study UWB channels over the surface of a human body. Parameters of a simple statistical path-loss model and their sensitivity to frequency and the location of the sensors on the body are discussed.