Observatorio de I+D+i UPM

Descripción
Wireless sensor networks are posed as the new communication paradigm where the use of small, low-complexity, and low-power devices is preferred over costly centralized systems. The spectra of potential applications of sensor networks is very wide, ranging from monitoring, surveillance, and localization, among others. Localization is a key application in sensor networks and the use of simple, efficient, and distributed algorithms is of paramount practical importance. Combining convex optimization tools with consensus algorithms we propose a distributed localization algorithm for scenarios where received signal strength indicator readings are used. We approach the localization problem by formulating an alternative problem that uses distance estimates locally computed at each node. The formulated problem is solved by a relaxed version using semidefinite relaxation technique. Conditions under which the relaxed problem yields to the same solution as the original problem are given and a distributed consensusbased implementation of the algorithm is proposed based on an augmented Lagrangian approach and primaldual decomposition methods. Although suboptimal, the proposed approach is very suitable for its implementation in real sensor networks, i.e., it is scalable, robust against node failures and requires only local communication among neighboring nodes. Simulation results show that running an additional local search around the found solution can yield performance close to the maximum likelihood estimate.
Internacional	Si
JCR del ISI	Si
Título de la revista	Eurasip Journal on Advances in Signal Processing
ISSN	1687-6180
Factor de impacto JCR	0,811
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Hasta la página	11
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• Autor: Benjamin Bejar (UPM)
• Autor: Santiago Zazo Bello (UPM)

• Creador: Grupo de Investigación: Grupo de Aplicaciones del Procesado de Señal (GAPS)
• Departamento: Señales, Sistemas y Radiocomunicaciones