Optimized edge appearance probability for cooperative localization based on tree-reweighted nonparametric belief propagation
Paper i proceeding, 2011

Nonparametric belief propagation (NBP) is a well-known particle-based method for distributed inference in wireless networks. NBP has a large number of applications, including cooperative localization. However, in loopy networks NBP suffers from similar problems as standard BP, such as over-confident beliefs and possible non-convergence. Tree-reweighted NBP (TRW-NBP) can mitigate these problems, but does not easily lead to a distributed implementation due to the non-local nature of the required so-called edge appearance probabilities. In this paper, we propose a variation of TRW-NBP, suitable for cooperative localization in wireless networks. Our algorithm uses a fixed edge appearance probability for every edge, and can outperform standard NBP in dense wireless networks.

tree-reweighted belief propagation

wireless networks

nonparametric belief propagation

Cooperative localization


Vladimir Savic

Universidad Politecnica de Madrid

Henk Wymeersch

Signaler och system, Kommunikationssystem, informationsteori och antenner, Kommunikationssystem

Federico Penna

Politecnico di Torino

Santiago Zazo

Universidad Politecnica de Madrid

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

15206149 (ISSN)

3028-3031 5946296


Data- och informationsvetenskap