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**Harvard**

Monir Vaghefi, S., Gholami, M., Buehrer, R. och Ström, E. (2013) *Cooperative Received Signal Strength-Based Sensor Localization with Unknown Transmit Powers*.

** BibTeX **

@article{

Monir Vaghefi2013,

author={Monir Vaghefi, Sayed Reza and Gholami, Mohammad Reza and Buehrer, R. Michael and Ström, Erik G.},

title={Cooperative Received Signal Strength-Based Sensor Localization with Unknown Transmit Powers},

journal={IEEE Transactions on Signal Processing},

issn={1053-587X},

volume={61},

issue={6},

pages={1389-1403},

abstract={Cooperative localization (also known as sensor network localization) using received signal strength (RSS) measurements when the source transmit powers are different and unknown is investigated. Previous studies were based on the assumption that the transmit powers of source nodes are the same and perfectly known which is not practical. In this paper, the source transmit powers are considered as nuisance parameters and estimated along with the source locations. The corresponding Cramer-Rao lower bound (CRLB) of the problem is derived. To find the maximum likelihood (ML) estimator, it is necessary to solve a nonlinear and nonconvex optimization problem, which is computationally complex. To avoid the difficulty in solving the ML estimator, we derive a novel semidefinite programming (SDP) relaxation technique by converting the ML minimization problem into a convex problem which can be solved efficiently. The algorithm requires only an estimate of the path loss exponent (PLE). We initially assume that perfect knowledge of the PLE is available, but we then examine the effect of imperfect knowledge of the PLE on the proposed SDP algorithm. The complexity analyses of the proposed algorithms are also studied in detail. Computer simulations showing the remarkable performance of the proposed SDP algorithm are presented.},

year={2013},

keywords={Computational complexity, cooperative sensor localization, linear least squares (LLS), maximum likelihood (ML), path loss exponent (PLE), Received Signal Strength (RSS), semidefinite programming (SDP), transmit power},

}

** RefWorks **

RT Journal Article

SR Electronic

ID 164545

A1 Monir Vaghefi, Sayed Reza

A1 Gholami, Mohammad Reza

A1 Buehrer, R. Michael

A1 Ström, Erik G.

T1 Cooperative Received Signal Strength-Based Sensor Localization with Unknown Transmit Powers

YR 2013

JF IEEE Transactions on Signal Processing

SN 1053-587X

VO 61

IS 6

SP 1389

OP 1403

AB Cooperative localization (also known as sensor network localization) using received signal strength (RSS) measurements when the source transmit powers are different and unknown is investigated. Previous studies were based on the assumption that the transmit powers of source nodes are the same and perfectly known which is not practical. In this paper, the source transmit powers are considered as nuisance parameters and estimated along with the source locations. The corresponding Cramer-Rao lower bound (CRLB) of the problem is derived. To find the maximum likelihood (ML) estimator, it is necessary to solve a nonlinear and nonconvex optimization problem, which is computationally complex. To avoid the difficulty in solving the ML estimator, we derive a novel semidefinite programming (SDP) relaxation technique by converting the ML minimization problem into a convex problem which can be solved efficiently. The algorithm requires only an estimate of the path loss exponent (PLE). We initially assume that perfect knowledge of the PLE is available, but we then examine the effect of imperfect knowledge of the PLE on the proposed SDP algorithm. The complexity analyses of the proposed algorithms are also studied in detail. Computer simulations showing the remarkable performance of the proposed SDP algorithm are presented.

LA eng

DO 10.1109/TSP.2012.2232664

LK http://dx.doi.org/10.1109/TSP.2012.2232664

LK http://publications.lib.chalmers.se/records/fulltext/local_164545.pdf

OL 30