Good error-correcting codes based on very sparse matrices
IEEE Transactions on Information Theory
The capacity of low-density parity-check codes under message-passing decoding
IEEE Transactions on Information Theory
Design of capacity-approaching irregular low-density parity-check codes
IEEE Transactions on Information Theory
Iterative Decoding With Replicas
IEEE Transactions on Information Theory
Efficient Serial Message-Passing Schedules for LDPC Decoding
IEEE Transactions on Information Theory
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In this paper, we propose a method for enhancing performance of a sequential version of the belief-propagation (BP) decoding algorithm, the group shuffled BP decoding algorithm for low-density parity-check (LDPC) codes. An improved BP decoding algorithm, called the shuffled BP decoding algorithm, decodes each symbol node in serial at each iteration. To reduce the decoding delay of the shuffled BP decoding algorithm, the group shuffled BP decoding algorithm divides all symbol nodes into several groups. In contrast to the original group shuffled BP, which automatically generates groups according to symbol positions, in this paper we propose a method for grouping symbol nodes which generates groups according to the structure of a Tanner graph of the codes. The proposed method can accelerate the convergence of the group shuffled BP algorithm and obtain a lower error rate in a small number of iterations. We show by simulation results that the decoding performance of the proposed method is improved compared with those of the shuffled BP decoding algorithm and the group shuffled BP decoding algorithm.