论文标题
通过卷积代码约束，改善广义LDPC代码的阈值
Improving the Thresholds of Generalized LDPC Codes with Convolutional Code Constraints
论文作者
论文摘要
CC-GLPDC代码是一类普遍的低密度奇迹检查（GLDPC）代码，其中约束节点（CNS）代表卷积代码。这允许使用前向后算法在格子中有效解码，并且可以轻松地通过编码器内存来控制组件代码的强度而无需更改图形结构。在这封信中，我们通过在中枢神经系统中引入不同类型的不规则性并研究了它们对二元擦除通道（BEC）的BP和MAP解码阈值的影响来扩展CC-GLDPC代码的类别。对于所考虑的代码类，进行详尽的网格搜索以找到BP优化和地图优化的合奏，并将其阈值与相同设计速率的常规集合进行比较。结果表明，不规则性可以显着改善BP阈值，而MAP优化集合的阈值仅与常规合奏略有不同。也提供了AWGN通道的仿真结果，并将其与相应的阈值进行了比较。
CC-GLPDC codes are a class of generalized low-density parity-check (GLDPC) codes where the constraint nodes (CNs) represent convolutional codes. This allows for efficient decoding in the trellis with the forward-backward algorithm, and the strength of the component codes easily can be controlled by the encoder memory without changing the graph structure. In this letter, we extend the class of CC-GLDPC codes by introducing different types of irregularity at the CNs and investigating their effect on the BP and MAP decoding thresholds for the binary erasure channel (BEC). For the considered class of codes, an exhaustive grid search is performed to find the BP-optimized and MAP-optimized ensembles and compare their thresholds with the regular ensemble of the same design rate. The results show that irregularity can significantly improve the BP thresholds, whereas the thresholds of the MAP-optimized ensembles are only slightly different from the regular ensembles. Simulation results for the AWGN channel are presented as well and compared to the corresponding thresholds.
