论文标题
记忆有效的相互信息最大化量化的Min-sum解码，以兼容速率的LDPC代码
Memory Efficient Mutual Information-Maximizing Quantized Min-Sum Decoding for Rate-Compatible LDPC Codes
论文作者
论文摘要
在这封信中，我们提出了一种两阶段的设计方法，以构建记忆有效的相互信息最大化量化的Min-sum（MIM-QMS）解码器，以构建与速率兼容的低密度平价检查（LDPC）代码。我们首先开发了修改的密度演变，以设计一组独特的查找表（LUTS），可用于兼容速率兼容的LDPC代码。根据其差异值和合并函数来优化构造的LUT，以减少内存要求。数值结果表明，与基于基准的基于LUT的解码器相比，提出的兼容速率的MIM-QMS解码器可以将解码的内存要求降低高达94.92％，其收敛速度通常更快。此外，所提出的解码器可以在0.15 dB内处理浮点信念传播解码器的性能。
In this letter, we propose a two-stage design method to construct memory efficient mutual information-maximizing quantized min-sum (MIM-QMS) decoder for rate-compatible low-density parity-check (LDPC) codes. We first develop a modified density evolution to design a unique set of lookup tables (LUTs) that can be used for rate-compatible LDPC codes. The constructed LUTs are optimized based on their discrepancy values and a merge function to reduce the memory requirement. Numerical results show that the proposed rate-compatible MIM-QMS decoder can reduce the memory requirement for decoding by up to 94.92% compared to the benchmark rate-compatible LUT-based decoder with generally faster convergence speed. In addition, the proposed decoder can approach the performance of the floating-pointing belief propagation decoder within 0.15 dB.
