LDPC码改进的量化自适应偏移最小和算法

Improved quantized adaptive-offset min-sum algorithm for low-density parity-check codes

为减小低密度奇偶校验(LDPC)码的量化译码算法的实现复杂度,提出了一种改进的4比特量化自适应偏移最小和(AOMS)译码算法。改进的AOMS译码算法中引入了预设的固定迭代次数作为启动偏移量修正因子自适应选择的条件;设计了一种4比特非均匀数据量化方案,保证量化数据的取值范围既能较好地满足外信息的动态范围,又能简单实现优化的量化偏移量修正因子。仿真结果表明,与浮点译码算法相比较,改进的量化AOMS译码算法的译码性能损失较小。

In order to reduce the implementation complexity of the quantized decoding algorithm for the Low-Density Parity-Check（LDPC）codes, an improved 4-bit quantized Adaptive-Offset Min-Sum（AOMS）algorithm is designed. The improved AOMS algorithm is obtained by introducing a pre-determined iteration number as the condition of adaptive selecting the offset factors. Furthermore, a 4-bit nonuniform quantization scheme is designed, which can guarantee the dynamic range of the extrinsic information and easily utilize the optimized quantized offset factors. The simulation results show that, compared with the floating-point decoding algorithms, the performance degradation of the improved 4-bit nonuniform quantized AOMS algorithm can be neglected.