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Uniformly Reweighted Belief Propagation for Estimation and Detection in Wireless Networks
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In this paper, we propose a new inference algorithm, suitable for distributed processing over wireless networks. The algorithm, called uniformly reweighted belief propagation (URWBP), 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 degree 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.
@article{WPS12urbp,
author = "H. Wymeersch and F. Penna and V. Savic",
title = "{Uniformly Reweighted Belief Propagation for Estimation and Detection in Wireless Networks}",
journal = "IEEE Transactions on Wireless Communications",
volume = "11",
number = "4",
pages = "1587-1595 ",
month = apr,
year = "2012",
}
Last modified 21.08.2012 14:46
Fokusseminar 02.11.2012
