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.

factor graph approach

sensor networks

belief propagation

sum-product algorithm


message passing

distributed detection

Distributed inference

approximate inference

factor graphs


multiple sensors


Henk Wymeersch

Signaler och system, Kommunikationssystem, informationsteori och antenner, 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 1587-1595 6153324


Data- och informationsvetenskap