Recently, a new structure of low density parity check (LDPC) code named raptor-like LDPC code has attracted much attention. It has better performance at low code rate. In this paper, a novel decoding scheme for raptor-like LDPC code is proposed. First, the Gaussian approximation density evolution (GADE) algorithm is used to track and analyze the message transmission during the decoding process. It is found that certain log likelihood ratio (LLR) messages can be approximated by “zero” setting in the early iteration of raptor-like LDPC decoding. In other words, some column and row operations could be eliminated without compromise the performance. Next, we propose a new decoding scheme, which can skip unnecessary column and row operations. In comparison with the traditional belief propagation (BP)-based LDPC decoding scheme, the proposed scheme can reduce the decoding complexity. Additionally, a new algorithm is developed to facilitate the selection of the early iteration number. With this novel design, the proposed decoding scheme performs almost the same as the traditional BP-based scheme. To proof the concept, the raptor-like LDPC codes in the ATSC3.0 digital TV system are used to evaluate the proposed scheme, in comparison with the traditional BP-based schemes, i.e., sum-product algorithm (SPA), offset min-sum algorithm (OMSA), and normalized min-sum algorithm (NMSA). The simulation results confirm that the proposed scheme can reduce the decoding complexity without sacrifice in performance for all SPA, OMSA, and NMSA methods. About 10% complexity reduction can be achieved. This will reduce the buttery consumption for Internet of Things (IoT) and handheld devices.

中文翻译：

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类 Raptor LDPC 码的低复杂度解码方案

最近，一种名为raptor-like LDPC码的低密度奇偶校验（LDPC）码的新结构引起了广泛关注。它在低码率下具有更好的性能。在本文中，提出了一种新的类似猛禽的 LDPC 码的解码方案。首先，使用高斯近似密度演化（GADE）算法对解码过程中的消息传输进行跟踪和分析。发现某些对数似然比（LLR）消息可以通过在类似猛禽的 LDPC 解码的早期迭代中设置“零”来近似。换句话说，可以在不影响性能的情况下消除一些列和行操作。接下来，我们提出了一种新的解码方案，可以跳过不必要的列和行操作。与传统的基于信念传播 (BP) 的 LDPC 解码方案相比，所提出的方案可以降低解码复杂度。此外，还开发了一种新算法来促进早期迭代次数的选择。通过这种新颖的设计，所提出的解码方案的性能几乎与传统的基于 BP 的方案相同。为了证明这个概念，与传统的基于 BP 的方案，即和积算法（SPA），偏移最小化算法相比，ATSC3.0 数字电视系统中的 raptor-like LDPC 码被用来评估所提出的方案。总和算法 (OMSA) 和归一化最小和算法 (NMSA)。仿真结果证实，所提出的方案可以在不牺牲所有 SPA、OMSA 和 NMSA 方法的性能的情况下降低解码复杂度。可以实现大约 10% 的复杂性降低。这将减少物联网 (IoT) 和手持设备的黄油消耗。