Optimized power allocation in nonlinear sensor networks via semidefinite programming

Rashid, U; Tuan, HD; Kha, HH

Optimized power allocation in nonlinear sensor networks via semidefinite programming

Rashid, U Tuan, HD

Kha, HH

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Publication Type:: Conference Proceeding
Citation:: IEEE Vehicular Technology Conference, 2010
Issue Date:: 2010-12-01

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Field	Value	Language
dc.contributor.author	Rashid, U	en_US
dc.contributor.author	Tuan, HD https://orcid.org/0000-0003-0292-6061	en_US
dc.contributor.author	Kha, HH	en_US
dc.date.issued	2010-12-01	en_US
dc.identifier.citation	IEEE Vehicular Technology Conference, 2010	en_US
dc.identifier.isbn	9781424435746	en_US
dc.identifier.issn	1550-2252	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16370
dc.description.abstract	This paper presents an efficient technique for power allocation to the sensor nodes in a nonlinear sensor network (NSN). We minimize mean square error of the estimation of a random scalar parameter subject to a constraint on total amount of power consumed by the sensor nodes. This estimation is carried out at fusion center (FC) which receives the local observations from the sensors located at different positions. We convert the optimization problem into a convex one, and then use semidefinite programming to find the global optimal solution. The simulation results show that our approach outperforms the previous work both for the channel with white noise and the one with colored noise. The proposed strategy also gives better results in case of nonlinear model when compared to the strategy of assigning equal power to sensor nodes. ©2010 IEEE.	en_US
dc.relation.ispartof	IEEE Vehicular Technology Conference	en_US
dc.relation.isbasedon	10.1109/VETECF.2010.5594512	en_US
dc.title	Optimized power allocation in nonlinear sensor networks via semidefinite programming	en_US
dc.type	Conference Proceeding
utslib.for	0902 Automotive Engineering	en_US
dc.location.activity	Ottawa, Canada	en_US
dc.location.activity	WOS:000221630800003
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

This paper presents an efficient technique for power allocation to the sensor nodes in a nonlinear sensor network (NSN). We minimize mean square error of the estimation of a random scalar parameter subject to a constraint on total amount of power consumed by the sensor nodes. This estimation is carried out at fusion center (FC) which receives the local observations from the sensors located at different positions. We convert the optimization problem into a convex one, and then use semidefinite programming to find the global optimal solution. The simulation results show that our approach outperforms the previous work both for the channel with white noise and the one with colored noise. The proposed strategy also gives better results in case of nonlinear model when compared to the strategy of assigning equal power to sensor nodes. ©2010 IEEE.

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http://hdl.handle.net/10453/16370