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Uniformly Reweighted Belief Propagation for Estimation and Detection in Wireless Networks

In this paper, we propose a new inference algorithm, suitable for distributed processing over wireless networks. The algorithm, called uniformly reweighted belief propagation (URW-BP), combines the local nature of belief propagation with the improved performance of tree-reweighted belief propagation...

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Bibliographic Details
Published in:IEEE transactions on wireless communications 2012-04, Vol.11 (4), p.1587-1595
Main Authors: Wymeersch, H., Penna, F., Savic, V.
Format: Article
Language:English
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Summary:In this paper, we propose a new inference algorithm, suitable for distributed processing over wireless networks. The algorithm, called uniformly reweighted belief propagation (URW-BP), combines the local nature of belief propagation with the improved performance of tree-reweighted belief propagation (TRW-BP) in graphs with cycles. It reduces the degrees of freedom in the latter algorithm to a single scalar variable, the uniform edge appearance probability ρ. We provide a variational interpretation of URW-BP, give insights into good choices of ρ, develop an extension to higher-order potentials, and complement our work with numerical performance results on three inference problems in wireless communication systems: spectrum sensing in cognitive radio, cooperative positioning, and decoding of a low-density parity-check (LDPC) code.
ISSN:1536-1276
1558-2248
1558-2248
DOI:10.1109/TWC.2012.021412.111509