Variant belief propagation (BP) algorithms are applied to low-density parity-check (LDPC) codes. However, conventional decoders suffer from a large resource consumption due to gathering messages from all the neighbour variable-nodes and/or check-nodes through cumulative calculations. In this paper, a check-belief propagation (CBP) decoding algorithm is proposed. Check-belief is used as the probability that the corresponding parity-check is satisfied. All check-beliefs are iteratively enlarged in a sequential recursive order, and successful decoding will be achieved after the check-beliefs are all big enough. Compared to previous algorithms employing a large number of cumulative calculations to gather all the neighbor messages, CBP decoding can renew each check-belief by propagating it from one check-node to another through only one variable-node, resulting in a low complexity decoding with no cumulative calculations. The simulation results and analyses show that the CBP algorithm provides little error-rate performance loss in contrast with the previous BP algorithms, but consumes much fewer calculations and memories than them. It earns a big benefit in terms of complexity.

翻译：变体置信传播（BP）算法被应用于低密度奇偶校验（LDPC）码。然而，传统译码器因需要通过累积计算从所有相邻变量节点和/或校验节点收集消息而面临大量资源消耗。本文提出一种检查置信传播（CBP）译码算法。检查置信度被定义为相应奇偶校验满足的概率。所有检查置信度以顺序递归方式迭代增大，当检查置信度均足够大时即可实现成功译码。与采用大量累积计算收集所有相邻消息的先前算法相比，CBP译码可通过仅经过一个变量节点将每个检查置信度从一个校验节点传播至另一节点，从而无需累积计算即可实现低复杂度译码。仿真结果与分析表明，CBP算法相较于先前的BP算法仅存在极小的误码率性能损失，但消耗的计算量与存储空间显著减少，在复杂度方面具有显著优势。