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 Conference on Antennas and Propagation 2012 - Prague, Czech Republic Duration: 26 Mar 2012 → 30 Mar 2012

Conference

Conference	6th European Conference on Antennas and Propagation 2012
Abbreviated title	EuCAP 2012
Country/Territory	Czech Republic
City	Prague
Period	26/03/2012 → 30/03/2012

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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.",

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Altvater, BHE, Heaney, SF, Cotton, SL, Meijerink, A, Bentum, MJ & Scanlon, WG 2012, RSSI-based environment identification for 2.45 GHz body area networks. in 2012 6th European Conference on Antennas and Propagation (EUCAP). pp. 755-759, 6th European Conference on Antennas and Propagation 2012, Prague, Czech Republic, 26/03/2012. https://doi.org/10.1109/EuCAP.2012.6206657

TY - CHAP

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

Y1 - 2012/3

N2 - 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.

AB - 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.

U2 - 10.1109/EuCAP.2012.6206657

DO - 10.1109/EuCAP.2012.6206657

M3 - Chapter

SN - 978-1-4577-0918-0

SP - 755

EP - 759

BT - 2012 6th European Conference on Antennas and Propagation (EUCAP)

T2 - 6th European Conference on Antennas and Propagation 2012

Y2 - 26 March 2012 through 30 March 2012

ER -

RSSI-based environment identification for 2.45 GHz body area networks

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