RSSI-based environment identification for 2.45 GHz body area networks

B.H.E. Altvater; S.F. Heaney; S.L. Cotton; A. Meijerink; M.J. Bentum; W.G. Scanlon

doi:10.1109/EuCAP.2012.6206657

RSSI-based environment identification for 2.45 GHz body area networks

B.H.E. Altvater, S.F. Heaney, S.L. Cotton, A. Meijerink, M.J. Bentum, W.G. Scanlon

Research output: Chapter in Book/Report/Conference proceeding › Chapter

1 Citation (Scopus)

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.

Original language	English
Title of host publication	2012 6th European Conference on Antennas and Propagation (EUCAP)
Pages	755-759
Number of pages	5
ISBN (Electronic)	978-1-4577-0919-7
DOIs	https://doi.org/10.1109/EuCAP.2012.6206657
Publication status	Published - Mar 2012
Event	6th European Conf. Antennas and Propagation (EUCAP) - Prague, Czech Republic Duration: 01 Mar 2012 → 01 Mar 2012

Conference

Conference	6th European Conf. Antennas and Propagation (EUCAP)
Country/Territory	Czech Republic
City	Prague
Period	01/03/2012 → 01/03/2012

Access to Document

10.1109/EuCAP.2012.6206657

Cite this

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title = "RSSI-based environment identification for 2.45 GHz body area networks",

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.",

author = "B.H.E. Altvater and S.F. Heaney and S.L. Cotton and A. Meijerink and M.J. Bentum and W.G. Scanlon",

year = "2012",

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T1 - RSSI-based environment identification for 2.45 GHz body area networks

AU - Altvater, B.H.E.

AU - Heaney, S.F.

AU - Cotton, S.L.

AU - Meijerink, A.

AU - Bentum, M.J.

AU - Scanlon, W.G.

PY - 2012/3

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