Low-Complexity Decoding Schemes for LDPC Codes Using Efficient Unreliable Path Search

Abstract

This dissertation contains the following contributions on the low-complexity decoding schemes of LDPC codes. Two-stage decoding scheme for LDPC codes – A new stopping criterion for LDPC codes – A new decoding scheme for LDPC codes with unreliable path search Parallel unreliable path search algorithm Analysis of two-stage decoding schemes – Validity and complexity analysis First, a new two-stage decoding scheme for low-density parity check (LDPC) codes to lower the error-floor is proposed. The proposed decoding scheme consists of the conventional belief propagation (BP) decoding algorithm as the first-stage decoding and the re-decodings with manipulated log-likelihood ratios (LLRs) of variable nodes as the second-stage decoding. In the first-stage decoding, an early stopping criterion is proposed for early detection of decoding failure and the candidate set of the variable nodes is determined, which can be partly included in the small trapping sets. In the second-stage decoding, the scores of the variable nodes in the candidate set are computed by the proposed unreliable path search algorithm and the variable nodes are sorted in ascending order by their scores for the re-decoding trials. Each re-decoding trial is performed by BP decoding algorithm with manipulated LLR of a selected variable node in the candidate set one at a time with the second early stopping criterion. Secondly, the parallel unreliable path search algorithm is proposed for practical application to the proposed unreliable path search algorithm. In order to reduce the decoding delay and computational complexity, an efficient method for the search algorithm based on the parallel message-passing algorithm in the LDPC decoding is proposed. The parallel unreliable path search algorithm significantly reduces the additional complexity without extra hardware requirements. Finally, the validity and the complexity analysis of the proposed unreliable path search algorithm is presented. The proposed algorithm effectively finds the variable nodes in small trapping sets much more faster than the previous random selection method. Also, it is verified that the additional complexity of the parallel unreliable path search algorithm is less than that of one iteration of iterative decoders.