Though belief propagation (BP) polar decoders can achieve higher throughput than successive-cancellation (SC)-based decoders, and how to efficiently generate different belief propagation decoders (BPDs) which can meet various design specifications remains challenging. To this end, an autogeneration, which can translate the generation formula of BPDs to efficient hardware implementations, has been proposed in this article. For different requirements, two BPD architectures have been given: 1) low-cost decoder (Type-I) and 2) high-throughput decoder (Type-II). The autogeneration of them can support different code rates, code lengths, and parallelisms. Synthesis results show that Type-I and Type-II provide higher throughput and hardware efficiency than the state-of-the-art (SOA) SC decoders. Moreover, compared to the SOA BPDs, both Type-I and Type-II achieve similar even better energy- and area-efficiency with a comparable throughput, for fully parallel configuration. With the autogeneration, we are able to obtain the design space regarding different design metrics, such as area efficiency, energy efficiency, and power density, within which the design optimization under given design constraints can be conducted.

中文翻译：

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流水线置信传播极性解码器的自动生成

尽管置信传播 (BP) 极性解码器可以实现比基于连续抵消 (SC) 的解码器更高的吞吐量，但如何有效地生成满足各种设计规范的不同置信传播解码器 (BPD) 仍然具有挑战性。为此，本文提出了一种自动生成，可以将 BPD 的生成公式转换为高效的硬件实现。针对不同的需求，给出了两种 BPD 架构：1) 低成本解码器 (Type-I) 和 2) 高吞吐量解码器 (Type-II)。它们的自动生成可以支持不同的码率、码长和并行度。综合结果表明，与最先进的 (SOA) SC 解码器相比，Type-I 和 Type-II 提供更高的吞吐量和硬件效率。此外，与 SOA BPD 相比，对于完全并行的配置，I 型和 II 型都实现了类似甚至更好的能量和面积效率以及可比的吞吐量。通过自动发电，我们能够获得关于不同设计指标的设计空间，例如面积效率、能源效率和功率密度，在这些空间内可以在给定的设计约束下进行设计优化。