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.
distributed detection
Distributed inference
factor graph approach
localization
sensor networks
sum-product algorithm
factor graphs
approximate inference
multiple sensors
belief propagation
message passing
models
Författare
Henk Wymeersch
Chalmers, Signaler och system, Kommunikation, Antenner och Optiska Nätverk
Federico Penna
Fraunhofer-Gesellschaft
Vladimir Savic
Universidad Politecnica de Madrid
IEEE Transactions on Wireless Communications
15361276 (ISSN) 15582248 (eISSN)
Vol. 11 4 1587-1595 6153324Coopnet
Europeiska kommissionen (EU) (EC/FP7/258418), 2011-05-01 -- 2016-04-30.
Robust och feltolerant kooperativ positionering
Vetenskapsrådet (VR) (2010-5889), 2011-01-01 -- 2013-12-31.
Ämneskategorier (SSIF 2011)
Data- och informationsvetenskap
DOI
10.1109/twc.2012.021412.111509