一种应用于不可分层LDPC码的并行分层译码算法

该文针对"不可分层"LDPC码无法利用分层算法进行译码的问题,提出了一种并行分层置信度传播(Parallel-Layered Belief-Propagation,PLBP)译码算法.与传统分层算法不同,该算法在译码时并行进行各层更新,串行进行层内各行更新.这种译码机制使得同一变量节点在各层内不同时进行更新,从而实现各变量节点在一次迭代中分层递进更新的算法目标.仿真表明,在不增加译码复杂度的情况下,该文提出的PLBP算法与传统的洪水算法相比,误码性能更优,而且所需要的平均迭代次数降低了约50%.此外,PLBP算法采用了合并的节点更新运算,最终使该算法达到的译码速度约为洪水算法的4倍.

A Parallel Layered Decoding Algorithm for Non-layered LDPC Codes

As layered algorithm can not be used in the decoding of the “non-layered” LDPC codes, a Parallel- Layered Belief-Propagation (PLBP) algorithm is proposed in this paper. The decoding of this algorithm is quite different from the original layered algorithm, for it uses parallel updating among all layers and serial updating within each layer. With such a decoding schedule, a variable node in different layers is updated at different time, which means the message is able to be updated layer by layer for each variable node. The simulation shows the PLBP algorithm not only achieves a better error performance, but also requires almost 50% less iterations than the Flooding algorithm with the same complexity. Additionally, a merged computation of the nodes is employed by the PLBP algorithm. As a result, the decoding speed of the PLBP algorithm can reach nearly 4 times as that of the original Flooding algorithm.