A New Density Evolution Approximation for LDPC and Multi-Edge Type LDPC Codes

作者：Jayasooriya Sachini^*; Shirvanimoghaddam Mahyar; Ong Lawrence; Lechner Gottfried; Johnson Sarah J

来源：IEEE Transactions on Communications, 2016, 64(10): 4044-4056.

DOI：10.1109/TCOMM.2016.2600660

• Belief-propagation
• density evolution
• Gaussian approximation
• low-density parity check (LDPC) codes
• multi-edge type LDPC codes

This paper considers density evolution for low-density parity-check (LDPC) and multi-edge type LDPC (MET-LDPC) codes over the binary input additive white Gaussian noise channel. We first analyze three single-parameter Gaussian approximations for density evolution and discuss their accuracy under several conditions, namely, at low rates, with punctured and degree-one variable nodes. We observe that the assumption of symmetric Gaussian distribution for the density-evolution messages is not accurate in the early decoding iterations, particularly at low rates and with punctured variable nodes. Thus, single-parameter Gaussian approximation methods produce very poor results in these cases. Based on these observations, we then introduce a new density evolution approximation algorithm for LDPC and MET-LDPC codes. Our method is a combination of full density evolution and a single-parameter Gaussian approximation, where we assume a symmetric Gaussian distribution only after density-evolution messages closely follow a symmetric Gaussian distribution. Our method significantly improves the accuracy of the code threshold estimation. Additionally, the proposed method significantly reduces the computational time of evaluating the code threshold compared with full density evolution thereby making it more suitable for code design.

• 出版日期2016-10