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IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences

Adaptive Decoding Algorithms for Low-Density Parity-Check Codes over the Binary Erasure Channel

Gou Hosoya, Hideki Yagi, Manabu Kobayashi, Shigeichi Hirasawa

Published Jan 1, 2009• 1 citation
Publisher

Abstract

Two decoding procedures combined with a belief-propagation (BP) decoding algorithm for low-density parity-check codes over the binary erasure channel are presented. These algorithms continue a decoding procedure after the BP decoding algorithm terminates. We derive a condition that our decoding algorithms can correct an erased bit which is uncorrectable by the BP decoding algorithm. We show by simulation results that the performance of our decoding algorithms is enhanced compared with that of the BP decoding algorithm with little increase of the decoding complexity.

DOI
10.1587/transfun.e92.a.2418

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Two decoding procedures combined with a belief-propagation (BP) decoding algorithm for low-density parity-check codes over the binary erasure channel are presented. These algorithms continue a decoding procedure after the BP decoding algorithm terminates. We derive a condition that our decoding algorithms can correct an erased bit which is uncorrectable by the BP decoding algorithm. We show by simulation results that the performance of our decoding algorithms is enhanced compared with that of the BP decoding algorithm with little increase of the decoding complexity.
In this correspondence, we first investigate some analytical aspects of the recently proposed improved decoding algorithm for low-density parity-check (LDPC) codes over the binary erasure channel (BEC). We derive a necessary and sufficient condition for the improved decoding algorithm to successfully complete decoding when the decoder is initialized to guess a predetermined number of guesses after the standard message-passing terminates at a stopping set. Furthermore, we present improved bounds on the number of bits to be guessed for successful completion of the decoding process when a stopping set is encountered. Under suitable conditions, we derive a lower bound on the number of iterations to be performed for complete decoding of the stopping set. We then present a superior, novel improved decoding algorithm for LDPC codes over the binary erasure channel (BEC). The proposed algorithm combines the observation that a considerable fraction of unsatisfied check nodes in the neighborhood of a stopping set are of degree two, and the concept of guessing bits to perform simple and intuitive graph-theoretic manipulations on the Tanner graph. The proposed decoding algorithm has a complexity similar to previous improved decoding algorithms. Finally, we present simulation results of short-length codes over BEC that demonstrate the superiority of our algorithm over previous improved decoding algorithms for a wide range of bit error rates
In this paper, we present a new low complexity decoding algorithm outperforming existing schemes. When the Belief Propagation fails and cannot solve all the erased bits, the guessing algorithm makes assumptions on a set of erased bits. However, in our new algorithm instead of guessing the values of a set of message bits, the decoder selects a set of check nodes and makes assumption on bits connected to them. The number of possibilities is reduced by half because the field is binary resulting in lower decoding complexity. The proposed decoding algorithm is applied to two regular half rate LDPC codes with lengths of 1000 and 2000. The theoretical belief propagation (BP) threshold for these two codes is 0.429. It is shown that the actual BP threshold is improved using the new algorithm. Setting the number of possibilities to two, we achieve a threshold of 0.43 which is higher than the BP theoretical.
This paper presents a new improved decoding algorithm for low-density parity-check (LDPC) codes over the binary erasure channel (BEC). The proposed algorithm combines the fact that a considerable fraction of unsatisfied check nodes are of degree two with the concept of guessing bits to perform simple graph-theoretic manipulations on the Tanner graph. The proposed decoding algorithm has a complexity similar to present improved decoding algorithms [H. Pishro-Nik et al., 2004]. Simulations of codes of very short lengths over BEC reveal the superiority of our algorithm over present improved decoding algorithms for a wide range of bit error rates.
A hybrid belief propagation (BP) decoding algorithm for low-density parity-check code is proposed to accelerate the convergence of decoding and reduce the number of decoding iterations. The hybrid scheme is presented by integrating the BP algorithm with the bit-flipping function which is used as adaptive weighted factor in the BP iteration decoding. The adaptive weighting factor is based on the average weighted reliability measure of the hard output of decoder. The proposed hybrid adaptive weighted iteration scheme can efficiently increase the convergence speed of the belief propagation decoding and therefore improve the error performance. Simulation results show that the proposed algorithm can significantly reduce the decoding complexity and achieve better error performances as compared with the sum-product algorithm.
In this paper, we propose a decoding algorithm which lowers decoding erasure rates in the error floor regions for non-binary low-density parity-check codes transmitted over the binary erasure channels. This decoding algorithm is a combination with belief propagation (BP) decoding and maximum a posteriori (MAP) decoding on zigzag cycles, which cause decoding erasures in the error floor region. We show that MAP decoding on the zigzag cycles is realized by means of a message passing algorithm. A simulation result shows that the decoding erasure rates in the error floor regions by the proposed decoding algorithm are lower than those by the BP decoder.