Cooperative Received Signal Strength-Based Sensor Localization with Unknown Transmit Powers
Artikel i vetenskaplig tidskrift, 2013

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.

path loss exponent (PLE)

Computational complexity

Received Signal Strength (RSS)

transmit power

semidefinite programming (SDP)

maximum likelihood (ML)

linear least squares (LLS)

cooperative sensor localization


Sayed Reza Monir Vaghefi

Virginia Polytechnic Institute and State University

Mohammad Reza Gholami

Chalmers, Signaler och system, Kommunikation, Antenner och Optiska Nätverk

R. Michael Buehrer

Virginia Polytechnic Institute and State University

Erik Ström

Chalmers, Signaler och system, Kommunikation, Antenner och Optiska Nätverk

IEEE Transactions on Signal Processing

1053-587X (ISSN)

Vol. 61 6 1389-1403 6375856


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