A Novel Nonparametric Messages Update Schedule in Graphical Model of LDPC-BICM

Compared to conventional message schedule in factor graph model of LDPC-BICM (low density parity-check coded Bit-Interleaved Coded Modulation) system, a novel nonparametric message update schedule is proposed to get a good trade-off between the performance and complexity. From a global perspective, a message update schedule with sparse channel estimation is designed by selecting different kinds of combination of the outer and inner iteration. And a partial selective message update schedule is designed from the local iterative decoding perspective by choosing proper comparison rule and threshold. In addition, a channel message update schedule is presented to prevent particle impoverishment and improve channel estimation precision by combining Markov Chain Monte Carlo (MCMC) particle filters (PF) into max-sum rule. Simulation results illustrate effectiveness and performance superiority of the proposed schedule compared to conventional schedule.