AI 中文总结
针对短LDPC码有限长度图效应问题，提出行增强集成置信传播译码算法，在5G NR码上显著降低误帧率，性能优于同等规模的同类算法，且具有可扩展性。
AI 中文摘要
短及中等长度低密度奇偶校验（LDPC）码的置信传播（BP）译码受有限长度图效应限制：即使存在可正确译码接收码字的替代轨迹，单个译码器轨迹仍可能陷入停滞或振荡。现有集成BP译码器通过多个奇偶校验矩阵、自同构、修正调度、子码或更新规则的变更来创造所需多样性。我们提出行增强集成（RBE）译码作为一种最小化的译码器侧多样性机制：所有集成成员共享同一奇偶校验矩阵和同一BP内核，仅在一小部分奇偶校验行的输出消息上存在差异。在5G NR BG1（144,96）码上，具有32个成员的RBE在E_b/N0=4.0dB时，将迭代20次的BP译码（BP-20）的误帧率从1.6×10^-2降至1.6×10^-3，性能优于同等规模的饱和最小和及仿射子码集成。集成规模增大可带来额外增益，表明RBE提供了可扩展的性能-复杂度权衡，该增益可跨5G NR块长度、码率、非5G短LDPC码以及洪水调度和分层调度转移。
英文摘要
Belief-propagation (BP) decoding of short and moderate-length low-density parity-check (LDPC) codes is limited by finite-length graph effects: a single decoder trajectory can become trapped or oscillatory even when an alternative trajectory would decode the received word. Existing ensemble-BP decoders create the required diversity through multiple parity-check matrices, automorphisms, modified schedules, subcodes, or altered update rules. We introduce row-boosted ensemble (RBE) decoding as a minimal decoder-side diversity mechanism: all ensemble members share the same parity-check matrix and the same BP kernel, and differ only in a small set of parity-check rows whose outgoing messages are boosted. On the 5G~NR BG1 \((144,96)\) code, RBE with \(32\) members lowers the frame-error rate of BP with \(20\) iterations (BP-20) from \(1.6\times10^{-2}\) to \(1.6\times10^{-3}\) at \(E_\mathrm{b}/N_0=4.0\,\mathrm{dB}\), outperforming saturated-min-sum and affine subcode ensembles of equal size. Increasing the ensemble size yields additional gains, indicating that RBE provides a scalable performance-complexity tradeoff. The gains transfer across 5G~NR block lengths and rates, to non-5G short LDPC codes, and across flooding and layered schedules.
Comments6 pages, 9 figures, submitted to an IEEE conference for possible publication
