Dynamical Behavior of Belief Propagation Detection Models in Massive MIMO Systems

Massive multiple input multiple output (MIMO) systems have been proposed as a potential method for high-capacity wireless communications. The belief propagation (BP) detection has recently attracted significant attention owing to its high estimation accuracy and practical computation time in MIMO systems. Although there is a choice of models for evaluating variances of residue components in the BP detection, no comparative analysis has thus far reported. In this study, we compare the bit error rate (BER) and dynamical behavior in iterative estimation among several models. Numerical results show that the models exhibit qualitatively different dynamical behaviors, which lead consequently different decoding accuracy among models. We also discuss potential improvements of the models based on the results.