Uniformly Reweighted Belief Propagation for Estimation and Detection in Wireless Networks
Artikel i vetenskaplig tidskrift, 2012

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 rho. We provide a variational interpretation of URW-BP, give insights into good choices of rho, 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.

belief propagation

distributed detection

sum-product algorithm

message passing

approximate inference


multiple sensors

factor graph approach


sensor networks

Distributed inference

factor graphs


Henk Wymeersch

Chalmers, Signaler och system, Kommunikations- och antennsystem, Kommunikationssystem

Federico Penna

Fraunhofer-Institut fur Nachrichtentechnik Heinrich-Hertz-Institut - HHI

Vladimir Savic

Universidad Politecnica de Madrid

IEEE Transactions on Wireless Communications

1536-1276 (ISSN)

Vol. 11 4 1587-1595 6153324

Robust och feltolerant kooperativ positionering

Vetenskapsrådet (VR), 2011-01-01 -- 2013-12-31.


Europeiska kommissionen (FP7), 2011-05-01 -- 2016-04-30.


Data- och informationsvetenskap



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