Knowledge-aided informed dynamic scheduling for LDPC decoding

Low-density parity-check (LDPC) codes offer excellent performance at competitive levels of complexity. Short block length LDPC codes avoid the large processing latency incurred by the large block lengths classically considered for this class of codes, making them a potential candidate for next generation wireless communications systems. In this paper, a novel informed dynamic scheduling (IDS) approach for decoding LDPC codes is developed based on the use of the current message reliabilities and the residuals of the potential updates to select the messages passed in the graph during iterative Sum Product decoding. An alternative measure of the iteration of the IDS schemes is also proposed which highlights the high cost of those algorithms in terms of processing complexity and motivates the development of the proposed approach. The proposed Rel.-RBP decoding algorithm offers very fast convergence at reduced complexity and gains in error rate performance when compared to the previous schemes.