Computer Science – Information Theory
Scientific paper
2012-02-07
Computer Science
Information Theory
Submitted for publication to the 2012 IEEE International Symposium on Information Theory, 5 pages, 3 figures
Scientific paper
We design iterative receiver schemes for a generic wireless communication system by treating channel estimation and information decoding as an inference problem in graphical models. We introduce a recently proposed inference framework that combines belief propagation (BP) and the mean field (MF) approximation and includes these algorithms as special cases. We also show that the expectation propagation and expectation maximization algorithms can be embedded in the BP-MF framework with slight modifications. By applying the considered inference algorithms to our probabilistic model, we derive four different message-passing receiver schemes. Our numerical evaluation demonstrates that the receiver based on the BP-MF framework and its variant based on BP-EM yield the best compromise between performance, computational complexity and numerical stability among all candidate algorithms.
Badiu Mihai-Alin
Fleury Bernard Henri
Kirkelund Gunvor Elisabeth
Manchón Carles Navarro
Riegler Erwin
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