Uniformly reweighted belief propagation: A factor graph approach
2011 (English)In: Proc. of IEEE Intl. Symp. on Information Theory Proceedings (ISIT), 2011, 2000-2004 p.Conference paper, Presentation (Refereed)
Tree-reweighted belief propagation is a message passing method that has certain advantages compared to traditional belief propagation (BP). However, it fails to outperform BP in a consistent manner, does not lend itself well to distributed implementation, and has not been applied to distributions with higher-order interactions. We propose a method called uniformly-reweighted belief propagation that mitigates these drawbacks. After having shown in previous works that this method can substantially outperform BP in distributed inference with pairwise interaction models, in this paper we extend it to higher-order interactions and apply it to LDPC decoding, leading performance gains over BP.
Place, publisher, year, edition, pages
2011. 2000-2004 p.
Belief propagation, Bit error rate, Decoding, Graphical models, Markov processes, Message passing, LDPC codes
Engineering and Technology Signal Processing Communication Systems
IdentifiersURN: urn:nbn:se:liu:diva-81417DOI: 10.1109/ISIT.2011.6033905ISBN: 978-1-4577-0596-0OAI: oai:DiVA.org:liu-81417DiVA: diva2:552304
IEEE Intl. Symp. on Information Theory Proceedings (ISIT), St. Petersburg, Russia