A Low Complexity MIMO Detection Based on Pairwise Markov Random Fields

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Executive Summary

Low complexity, iterative MIMO detection algorithms are derived based on pair-wise Markov Random Fields (MRF). The authors consider two types, namely, the fully-connected and the ring type MRF and, for the edge potentials, they use the bi-variate Gaussian function obtained by marginalizing the posterior joint probability density under Gaussian-input assumption. Since the corresponding factor graphs has only 2 edges per factor node, the computations are much easier than that of ML which is similar to the belief propagation algorithm run over the fully connected factor graph.

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