Title :
On energy-based localization in wireless sensor networks
Author_Institution :
Univ. Lusofona de Humanidades e Tecnol., Lisbon, Portugal
Abstract :
In this paper, the energy-based localization problem in wireless sensor networks is addressed. The maximum likelihood (ML) location estimation problem is a difficult optimization problem due to the non-convexity of the objective function, and an exact solution is difficult to obtain. An approximate solution to the ML problem is proposed, by relaxing the minimization problem into semidefinite programming form. Simulation results show that the proposed algorithm outperforms the existing solutions.
Keywords :
approximation theory; mathematical programming; maximum likelihood estimation; sensor placement; wireless sensor networks; ML problem; energy-based localization problem; maximum likelihood location estimation problem; minimization problem; objective function nonconvexity; optimization problem; semidefinite programming; wireless sensor network; Convex functions; Minimization; Noise level; Optimization; Position measurement; Wireless sensor networks; Semidefinite relaxation; Sensor networks; Source localization;
Conference_Titel :
Signal Processing Advances in Wireless Communications (SPAWC), 2011 IEEE 12th International Workshop on
Conference_Location :
San Francisco, CA
Print_ISBN :
978-1-4244-9333-3
Electronic_ISBN :
1948-3244
DOI :
10.1109/SPAWC.2011.5990379
