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首页> 外文会议>Annual Allerton Conference on Communication, Control, and Computing; 20040929-1001; Monticello,IL(US) >Mean Field and Mixed Mean Field Iterative Decoding of Low-Density Parity-Check Codes
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Mean Field and Mixed Mean Field Iterative Decoding of Low-Density Parity-Check Codes

机译：低密度奇偶校验码的均值和混合均值迭代解码

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摘要

In this paper, employment of the mean field and mixed mean field algorithms for decoding low-density parity-check codes is discussed. The mean field principle is well established in statistical physics and artificial intelligence. Instead of using a single completely factorized approximated distribution as in the mean field approach, the mixed mean field algorithm forms a weighted average of several mean field distributions as an approximation of the true posterior probability distribution. The mean field decoding algorithm for linear block codes is derived and shown to be an approximation of the a posterior probability decoding algorithm. The mean field approach is then developed in the context of iterative decoding and presented as an approximation of the popular belief propagation decoding method. Simulation results are presented to show that the mean field and mixed mean field decoding algorithms yield a good performance-complexity trade-off, especially when employed for decoding low-density parity-check codes based on finite geometries.
机译：本文讨论了采用均值域和混合均值域算法对低密度奇偶校验码进行解码的方法。平均场原理在统计物理学和人工智能中已得到很好的确立。代替在均值场方法中使用单个完全分解的近似分布，混合均值场算法形成几个均值场分布的加权平均值，作为真实后验概率分布的近似值。推导了用于线性分组码的平均场解码算法，并将其示为后验概率解码算法的近似值。然后，在迭代解码的上下文中开发了均值场方法，并将其作为流行的信念传播解码方法的近似表示。仿真结果表明，平均场和混合平均场解码算法具有良好的性能复杂度折衷，特别是在基于有限几何结构的低密度奇偶校验码解码中。

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