Further Results on LDPC Decoding Scheduling for Faster Convergence

This paper presents a listed maximum mutual information increase ((LMI2)-I-2)-based algorithm, which is used to arrange low-density parity-check (LDPC) decoding schedules for faster convergence. The increments in the predicted mutual information for the messages to be updated is used to guide the arrangement of the fixed decoding schedule. Consequently, by looking ahead for several decoding stages, a high-order prediction can be realized. For each decoding stages, the searching branches can be trimmed to fit a predetermined size of list, and the efficiency in the selection of update candidates is thus increased. Comparing to previous algorithms, the proposed (LMI2)-I-2-based algorithm can be used to arrange the decoding schedules converged in the same speed with lower complexity, or accelerate the convergence with the same computation cost.