RSSI-based environment identification for 2.45 GHz. body area networks


Altvater, B.H.E. and Heaney, S.F. and Cotton, S.L. and Meijerink, A. and Bentum, M.J. and Scanlon, W.G. (2012) RSSI-based environment identification for 2.45 GHz. body area networks. In: IEEE 6th European Conference on Antennas and Propagation (EUCAP2012), 26-30 March 2012, Prague, Czech Republic (pp. pp. 755-759).

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Abstract:Abstract—A unique property of body area networks (BANs) is the mobility of the network as the user moves freely around. This mobility represents a significant challenge for BANs, since, in order to operate efficiently, they need to be able to adapt to the changing propagation environment. A method is presented that allows BAN nodes to classify the current operating environment in terms of multipath conditions, based on received signal strength indicator values during normal packet transmissions. A controlled set of measurements was carried out to study the effect different environments inflict on on-body link signal strength in a 2.45 GHz BAN. The analysis shows that, by using two statistical parameters, gathered over a period of one second, BAN nodes can successfully classify the operating environment for over 90% of the time.
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Electrical Engineering, Mathematics and Computer Science (EEMCS)
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