Knowledge‐aided iterative detection and decoding for multiuser multiple‐antenna systems

Abstract

In this work, the authors assess the performance and latency of a receiver design for multiuser multiple-antenna systems using low-density parity-check (LDPC) codes with iterative detection and decoding (IDD). The proposed knowledge-aided IDD (KA-IDD) receiver employs a parallel interference cancellation detector with refined iterative processing and a reweighted belief propagation (BP) decoder. Additionally, two BP-based decoding algorithms are proposed for improved performance of the decoder. The first cycle knowledge-aided reweighted-BP decoder takes advantage of the information about the distribution of cycles in the Tanner graph and the second expansion knowledge-aided reweighted-BP decoder expands the original graph into a set of subgraphs, then locally optimises the reweighting parameters of each subgraph. Novel reweighting parameter optimisation strategies are developed for decoding regular or irregular LDPC codes. The developed schemes optimise the parameters off-line and neither of these proposed algorithms imposes extra computational complexity to the on-line decoding procedure. Furthermore, the proposed schemes reduce the decoding latency. Simulation results show that the proposed KA-IDD scheme and algorithms outperform prior art and require a reduced number of decoding iterations.