TY - GEN

T1 - Message-Passing Algorithms for Channel Estimation and Decoding Using Approximate Inference

A1 - Badiu,Mihai Alin

A1 - Kirkelund,Gunvor Elisabeth

A1 - Manchón,Carles Navarro

A1 - Riegler,Erwin

A1 - Fleury,Bernard Henri

AU - Badiu,Mihai Alin

AU - Kirkelund,Gunvor Elisabeth

AU - Manchón,Carles Navarro

AU - Riegler,Erwin

AU - Fleury,Bernard Henri

PB - IEEE Press

PY - 2012/7

Y1 - 2012/7

N2 - We design iterative receiver schemes for a generic 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 (EM) 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 in a wireless scenario 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.

AB - We design iterative receiver schemes for a generic 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 (EM) 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 in a wireless scenario 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.

U2 - 10.1109/ISIT.2012.6283939

DO - 10.1109/ISIT.2012.6283939

SN - 978-1-4673-2580-6

BT - IEEE International Symposium on Information Theory

T2 - IEEE International Symposium on Information Theory

T3 - Proceedings of the IEEE International Symposium on Information Theory

T3 - en_GB

SP - 2376

EP - 2380

ER -