Improved Large-MIMO Detection Based on Damped Belief Propagation
In this paper, the authors consider the application of Belief Propagation (BP) to achieve near-optimal signal detection in large Multiple-Input Multiple-Output (MIMO) systems at low complexities. Large-MIMO architectures based on spatial multiplexing (V-BLAST) as well as non-orthogonal Space-Time Block Codes (STBC) from Cyclic Division Algebra (CDA) are considered. They adopt graphical models based on Markov Random Fields (MRF) and Factor Graphs (FG). In the MRF based approach, they use pairwise compatibility functions although the graphical models of MIMO systems are fully/densely connected. In the FG approach, they employ a Gaussian Approximation (GA) of the multi-antenna interference, which significantly reduces the complexity while achieving very good performance for large dimensions.