快速低密度校验码迭代译码量化算法

提出一种低密度校验码快速量化置信传播译码算法，其中量化电平标号作为定点算术操作数，运算由寻址表完成，中间计算以较高精度包含在表中，该算法具有明显低的时间复杂度，应用对称特性，可以显著降低所需存储容量；在不增加复杂度的前提下，可以方便地实现均匀及各种为改进性能而设计的非均匀量化方案；适当增加复杂度还可实现时变译码，该算法使低密度校验码在实际通信系统中的应用比时已经接近连续译码，而高信誉噪比时比连续译码差0.2dB。合适的高阶量化译码可以获得接近连续译码的性能，高信噪比时甚至优于连续译码。

Fast quantized belief propagation algorithm for iteratively decoding LDPC codes

A fast quantized belief propagation algorithm is proposed for decoding low-density parity-check(LDPC) codes. With operations performed by addressing tables, the proposed algorithm takes as operands the indices of labels rather than the quantization levels. The intermediate calculations have been contained in operation tables with much higher precision. The required storage can be significantly reduced by applying the symmetry property while keeping low time complexity. Without the increase in time complexity, it is convenient to realize the decoding with uniform quantization or any nonuniform quantizations that is designed for improving the performance. The time-varying decoder also becomes possible. This algorithm makes it possible to apply LDPC codes to practical systems or to realize fast simulation systems. Some simulation results are also given. The 6?bit logarithmic quantization results in gains of about 0.2?dB relative to the uniform one, approaching to the continuous decoding at low signal-to-noise ratios (SNRs) and yielding a loss of about 0.2?dB at high SNRs. Proper quantization of high order can achieve the performance of continuous decoding, and it may be superior to continuous decoding at high SNRs.