RSSI-based environment identification for 2.45 GHz body area networks

Bernhard H.E. Altvater; Sean F. Heaney; Simon L. Cotton; Arjan Meijerink; Mark J. Bentum; William G. Scanlon

doi:10.1109/EuCAP.2012.6206657

RSSI-based environment identification for 2.45 GHz body area networks

Bernhard H.E. Altvater
, Sean F. Heaney
, Simon L. Cotton
, Arjan Meijerink
, Mark J. Bentum
, William G. Scanlon

Research output: Chapter in Book/Report/Conference proceedings › Conference proceeding › peer-review

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	Proceedings of 6th European Conference on Antennas and Propagation, EuCAP 2012
Pages	755-759
Number of pages	5
DOIs	https://doi.org/10.1109/EuCAP.2012.6206657
Publication status	Published - 2012
Externally published	Yes
Event	6th European Conference on Antennas and Propagation, EuCAP 2012 - Prague, Czech Republic Duration: 26 Mar 2012 → 30 Mar 2012

Publication series

Name	Proceedings of 6th European Conference on Antennas and Propagation, EuCAP 2012

Conference

Conference	6th European Conference on Antennas and Propagation, EuCAP 2012
Country/Territory	Czech Republic
City	Prague
Period	26/03/12 → 30/03/12

Keywords

BAN
environment identification
mean
RSSI
variance

Access to Document

10.1109/EuCAP.2012.6206657

Cite this

Altvater, B. H. E., Heaney, S. F., Cotton, S. L., Meijerink, A., Bentum, M. J., & Scanlon, W. G. (2012). RSSI-based environment identification for 2.45 GHz body area networks. In Proceedings of 6th European Conference on Antennas and Propagation, EuCAP 2012 (pp. 755-759). Article 6206657 (Proceedings of 6th European Conference on Antennas and Propagation, EuCAP 2012). https://doi.org/10.1109/EuCAP.2012.6206657

@inproceedings{8631d03e8db04deea87f2a54b9c7e109,

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.",

keywords = "BAN, environment identification, mean, RSSI, variance",

author = "Altvater, \{Bernhard H.E.\} and Heaney, \{Sean F.\} and Cotton, \{Simon L.\} and Arjan Meijerink and Bentum, \{Mark J.\} and Scanlon, \{William G.\}",

year = "2012",

doi = "10.1109/EuCAP.2012.6206657",

language = "English",

isbn = "9781457709180",

series = "Proceedings of 6th European Conference on Antennas and Propagation, EuCAP 2012",

pages = "755--759",

booktitle = "Proceedings of 6th European Conference on Antennas and Propagation, EuCAP 2012",

note = "6th European Conference on Antennas and Propagation, EuCAP 2012 ; Conference date: 26-03-2012 Through 30-03-2012",

}

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 Proceedings of 6th European Conference on Antennas and Propagation, EuCAP 2012., 6206657, Proceedings of 6th European Conference on Antennas and Propagation, EuCAP 2012, pp. 755-759, 6th European Conference on Antennas and Propagation, EuCAP 2012, Prague, Czech Republic, 26/03/12. https://doi.org/10.1109/EuCAP.2012.6206657

RSSI-based environment identification for 2.45 GHz body area networks. / Altvater, Bernhard H.E.; Heaney, Sean F.; Cotton, Simon L. et al.
Proceedings of 6th European Conference on Antennas and Propagation, EuCAP 2012. 2012. p. 755-759 6206657 (Proceedings of 6th European Conference on Antennas and Propagation, EuCAP 2012).

Research output: Chapter in Book/Report/Conference proceedings › Conference proceeding › peer-review

TY - GEN

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

AU - Altvater, Bernhard H.E.

AU - Heaney, Sean F.

AU - Cotton, Simon L.

AU - Meijerink, Arjan

AU - Bentum, Mark J.

AU - Scanlon, William G.

PY - 2012

Y1 - 2012

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.

KW - BAN

KW - environment identification

KW - mean

KW - RSSI

KW - variance

UR - https://www.scopus.com/pages/publications/84862900171

U2 - 10.1109/EuCAP.2012.6206657

DO - 10.1109/EuCAP.2012.6206657

M3 - Conference proceeding

AN - SCOPUS:84862900171

SN - 9781457709180

T3 - Proceedings of 6th European Conference on Antennas and Propagation, EuCAP 2012

SP - 755

EP - 759

BT - Proceedings of 6th European Conference on Antennas and Propagation, EuCAP 2012

T2 - 6th European Conference on Antennas and Propagation, EuCAP 2012

Y2 - 26 March 2012 through 30 March 2012

ER -

RSSI-based environment identification for 2.45 GHz body area networks

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this