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.

nonparametric belief propagation

tree-reweighted belief propagation

Cooperative localization

wireless networks


Vladimir Savic

Universidad Politecnica de Madrid

Henk Wymeersch

Chalmers, Signaler och system, Kommunikations- och antennsystem, 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





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