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Reduced Complexity Belief Propagation Algorithm Based on Iterative Groupwise Multiuser Detection

We propose a new method to reduce the complexity of belief propagation algorithm (BP) using an iterative groupwise multiuser detection approach. Replacing the optimal joint maximum a posteriori (JMAP) detectors in BP function nodes by the iterative multiuser detection algorithm (IMUD) reduces the computational load of BP. We explain why IMUD is a good choice for this task and investigate the performance of this reduced complexity BP via simulation.