LDPC Decoding Scheduling for Faster Convergence and Lower Error Floor.

This paper presents a maximum mutual information increase (M^2I^2)-based algorithm that can be used to arrange low-density parity-check (LDPC) decoding schedules for faster convergence, where the increase is used to guide the arrangement of the fixed decoding schedule. The predicted mutual information for the messages to be updated is used in the calculation of the increase. By looking ahead for several decoding stages, a high-order prediction can be realized, which can then be used to devise a schedule with an even faster convergence. For a single received frame, different decoding results can be obtained using different schedules, and, hence, schedule diversity, that lowers the error floor resultant from the dominant trapping sets, is proposed. By adopting the M^2I^2-based schedule together with the schedule diversity, both the convergence speed in the waterfall region and the error-rate in the floor region can be improved. [ABSTRACT FROM AUTHOR]