Regression-based transmission power control for green healthcare

Noman Zahid; Ali Hassan Sodhro; Raja Fawad Zafar; Bilal Zahid; Saeed Ahmed Khan; Faheem Akhter

doi:10.1109/ICOMET.2019.8673532

Regression-based transmission power control for green healthcare

Noman Zahid, Ali Hassan Sodhro, Raja Fawad Zafar, Bilal Zahid, Saeed Ahmed Khan, Faheem Akhter

Forskningsoutput: Konferensbidrag › Arbetsdokument (paper) › Peer review

8 Citeringar (Scopus)

Sammanfattning

Energy saving is the dire need of resource-constrained wearable healthcare sensors. Classical methods are inappropriate to fulfill the needs of healthcare platform especially, body sensor networks (BSNs). So, to remedy the energy crises issues this paper proposes regression-based Self-Predictive Power Control (SPPC) algorithm by incorporating power levels in association to dynamic wireless channel. Besides, two experimental scenarios; 'Right Wrist to Chest' and 'Right Ankle to Chest' are adopted, it is examined through extensive simulation results that proposed SPPC has better performance unlike their counterparts such as, APC. Thus, proposed regression-based SPPC is the suitable candidate for the emerging healthcare applications.

Originalspråk	Engelska
DOI	https://doi.org/10.1109/ICOMET.2019.8673532
Status	Publicerad - 2019-mars-22
Externt publicerad	Ja
Evenemang	2nd International Conference on Computing, Mathematics and Engineering Technologies, iCoMET 2019 - Sukkur, Pakistan Varaktighet: 2019-jan.-30 → 2019-jan.-31

Konferens

Konferens	2nd International Conference on Computing, Mathematics and Engineering Technologies, iCoMET 2019
Land/Territorium	Pakistan
Ort	Sukkur
Period	19-01-30 → 19-01-31

Nationell ämneskategori

Kommunikationssystem (20203)

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10.1109/ICOMET.2019.8673532

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@conference{5c5524a65036482fae7a5fbf611207b8,

title = "Regression-based transmission power control for green healthcare",

abstract = "Energy saving is the dire need of resource-constrained wearable healthcare sensors. Classical methods are inappropriate to fulfill the needs of healthcare platform especially, body sensor networks (BSNs). So, to remedy the energy crises issues this paper proposes regression-based Self-Predictive Power Control (SPPC) algorithm by incorporating power levels in association to dynamic wireless channel. Besides, two experimental scenarios; 'Right Wrist to Chest' and 'Right Ankle to Chest' are adopted, it is examined through extensive simulation results that proposed SPPC has better performance unlike their counterparts such as, APC. Thus, proposed regression-based SPPC is the suitable candidate for the emerging healthcare applications.",

keywords = "ACK, APC, BSNs, Green, Healthcare, Regression, SPPC, TPC",

author = "Noman Zahid and Sodhro, {Ali Hassan} and {Fawad Zafar}, Raja and Bilal Zahid and Khan, {Saeed Ahmed} and Faheem Akhter",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2nd International Conference on Computing, Mathematics and Engineering Technologies, iCoMET 2019 ; Conference date: 30-01-2019 Through 31-01-2019",

year = "2019",

month = mar,

day = "22",

doi = "10.1109/ICOMET.2019.8673532",

language = "English",

}

TY - CONF

T1 - Regression-based transmission power control for green healthcare

AU - Zahid, Noman

AU - Sodhro, Ali Hassan

AU - Fawad Zafar, Raja

AU - Zahid, Bilal

AU - Khan, Saeed Ahmed

AU - Akhter, Faheem

PY - 2019/3/22

Y1 - 2019/3/22

N2 - Energy saving is the dire need of resource-constrained wearable healthcare sensors. Classical methods are inappropriate to fulfill the needs of healthcare platform especially, body sensor networks (BSNs). So, to remedy the energy crises issues this paper proposes regression-based Self-Predictive Power Control (SPPC) algorithm by incorporating power levels in association to dynamic wireless channel. Besides, two experimental scenarios; 'Right Wrist to Chest' and 'Right Ankle to Chest' are adopted, it is examined through extensive simulation results that proposed SPPC has better performance unlike their counterparts such as, APC. Thus, proposed regression-based SPPC is the suitable candidate for the emerging healthcare applications.

AB - Energy saving is the dire need of resource-constrained wearable healthcare sensors. Classical methods are inappropriate to fulfill the needs of healthcare platform especially, body sensor networks (BSNs). So, to remedy the energy crises issues this paper proposes regression-based Self-Predictive Power Control (SPPC) algorithm by incorporating power levels in association to dynamic wireless channel. Besides, two experimental scenarios; 'Right Wrist to Chest' and 'Right Ankle to Chest' are adopted, it is examined through extensive simulation results that proposed SPPC has better performance unlike their counterparts such as, APC. Thus, proposed regression-based SPPC is the suitable candidate for the emerging healthcare applications.

KW - ACK

KW - APC

KW - BSNs

KW - Green

KW - Healthcare

KW - Regression

KW - SPPC

KW - TPC

U2 - 10.1109/ICOMET.2019.8673532

DO - 10.1109/ICOMET.2019.8673532

M3 - Paper

AN - SCOPUS:85064115058

T2 - 2nd International Conference on Computing, Mathematics and Engineering Technologies, iCoMET 2019

Y2 - 30 January 2019 through 31 January 2019

ER -

Regression-based transmission power control for green healthcare

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