Uniformly Reweighted Belief Propagation for Estimation and Detection in Wireless Networks
Journal article, 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
Author
Henk Wymeersch
Chalmers, Signals and Systems, Communication, Antennas and Optical Networks
Federico Penna
Fraunhofer Society
Vladimir Savic
Technical University of Madrid
IEEE Transactions on Wireless Communications
15361276 (ISSN) 15582248 (eISSN)
Vol. 11 4 1587-1595 6153324Cooperative Situational Awareness for Wireless Networks (COOPNET)
European Commission (EC) (EC/FP7/258418), 2011-05-01 -- 2016-04-30.
Robust and Fault-Tolerant Cooperative Positioning
Swedish Research Council (VR) (2010-5889), 2011-01-01 -- 2013-12-31.
Subject Categories (SSIF 2011)
Computer and Information Science
DOI
10.1109/twc.2012.021412.111509