Joint MIMO Detection and LDPC Decoding Via Enhanced Belief Propagation for 5G-NR

In this paper, we consider joint MIMO detection and LDPC decoding on a tripartite factor graph. Conventional method in this regard design a belief propagation (BP) detector that applies an matched filtering detection per layer by subtracting interferences from other layers, which is suboptimal. Further, the BP scheduling between detection and decoding is unoptimized, which makes the interaction less effective. To overcome these issues, we propose to enhance the BP based joint detection and decoding (BP-JDD) receiver with 4 different techniques: pre-filtering (PF), partial marginalization (PM), hybrid updating schedule (HUS) and damping. Among them, PF and PM can improve the BP detection under challenging conditions, such as correlated MIMO channels, high-order modulations, or high code-rates, while HUS and damping are effective to accelerate convergence and reduce the number of overall iterations for BP-JDD to succeed. Combining these 4 techniques yields an enhanced BP-JDD design that can provide significant performance gains over traditional turbo receivers, and is also robust against channel variations.