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非对称无记忆信道的密度演化

Density Evolution for Asymmetric Memoryless Channels

C. -C. Wang, S. R. Kulkarni, H. V. Poor

摘要:

密度演化是研究低密度奇偶校验(LDPC)码和具有消息传递译码算法的图码的最有力的分析工具之一。以信道对称性为基本假设的密度演化(DE)已被广泛应用于不同的信道,包括二进制擦除信道、二进制对称信道、二进制加性高斯白噪声信道等。本文将非对称无记忆信道的密度演化推广到一般无记忆信道,如z信道,复合高斯白噪声信道等。支持这种推广的中心定理是收敛到任何固定大小的支持树的完美投影。给出了一个新的具有相同复杂度的迭代公式,并给出了性能集中定理的必要定理。新的密度演化方法的几个属性进行了探讨,包括一般的非对称无记忆通道的稳定性结果。模拟,代码优化,并提出了这种新的密度演化方法可能的新应用。这一结果也被用来证明线性LDPC码的典型性陪集码集成时,最小校验节点的程度是足够大的。它表明,收敛到完美的投影是必不可少的信念传播算法,即使只考虑对称通道。因此,收敛到完美投影的证明也是对对称无记忆通道经典密度演化理论的完善。

英文摘要:

Density evolution is one of the most powerful analytical tools for low-density parity-check (LDPC) codes and graph codes with message passing decoding algorithms. With channel symmetry as one of its fundamental assumptions, density evolution (DE) has been widely and successfully applied to different channels, including binary erasure channels, binary symmetric channels, binary additive white Gaussian noise channels, etc. This paper generalizes density evolution for non-symmetric memoryless channels, which in turn broadens the applications to general memoryless channels, e.g. z-channels, composite white Gaussian noise channels, etc. The central theorem underpinning this generalization is the convergence to perfect projection for any fixed size supporting tree. A new iterative formula of the same complexity is then presented and the necessary theorems for the performance concentration theorems are developed. Several properties of the new density evolution method are explored, including stability results for general asymmetric memoryless channels. Simulations, code optimizations, and possible new applications suggested by this new density evolution method are also provided. This result is also used to prove the typicality of linear LDPC codes among the coset code ensemble when the minimum check node degree is sufficiently large. It is shown that the convergence to perfect projection is essential to the belief propagation algorithm even when only symmetric channels are considered. Hence the proof of the convergence to perfect projection serves also as a completion of the theory of classical density evolution for symmetric memoryless channels.

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