Non-parametric belief propagation (NBP) is a well-known message passing method for cooperative localization in wireless networks. However, due to the over-counting problem in the networks with loops, NBP’s convergence is not guaranteed, and its estimates are typically less accurate. One solution for this problem is non-parametric generalized belief propagation based on junction tree. However, this method is intractable in large-scale networks due to the high-complexity of the junction tree formation, and the high-dimensionality of the particles. Therefore, in this article, we propose the non-parametric generalized belief propagation based on pseudo-junction tree (NGBP-PJT). The main difference comparing with the standard method is the formation of pseudo-junction tree, which represents the approximated junction tree based on thin graph. In addition, in order to decrease the number of high-dimensional particles, we use more informative importance density function, and reduce the dimensionality of the messages. As by-product, we also propose NBP based on thin graph (NBP-TG), a cheaper variant of NBP, which runs on the same graph as NGBP-PJT. According to our simulation and experimental results, NGBP-PJT method outperforms NBP and NBP-TG in terms of accuracy, computational, and communication cost in reasonably sized networks. / COOPLOC / FP7-ICT WHERE2
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-88543 |
| Date | January 2013 |
| Creators | Savic, Vladimir, Zazo, Santiago |
| Publisher | Linköpings universitet, Kommunikationssystem, Linköpings universitet, Tekniska högskolan, Technical University of Madrid, Spain |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Article in journal, info:eu-repo/semantics/article, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | EURASIP Journal on Advances in Signal Processing, 1687-6172, 2013, 16, |
Page generated in 0.0015 seconds