Single edge based belief propagation algorithms for MIMO detection

In this paper, two low-complexity belief propagation (BP) based detectors are proposed for multiple-input multiple-out (MIMO) system. The factor graph is leveraged to represent the MIMO channels, and based on which our algorithms are developed. Unlike the existing complicated standard BP detectors that consider all the edges when updating the messages, our algorithms only focus on single edge, which largely reduce computational complexity. In particular, we propose a novel Gaussian approximation with feedback information (GF) mechanism to enable the proposed single edge BP detector. In order to further improve the detection performance, we also propose to integrate the linear MIMO detector into the initial GF based single edge BP detector, where the pseudo priori (PP) information obtained from linear detector is judiciously exploited. Convergence and complexity analyses, along with the numerical simulations, verify that the proposed single edge BP detectors outperform the existing BP detectors in performance while with low complexity.