论文标题
典型的错误指数：双域推导
Typical Error Exponents: A Dual Domain Derivation
论文作者
论文摘要
本文表明，从成对独立合奏随机生成的给定代码的误差指数小于典型随机编码指数上的下限，因为代码字趋于无限。已知该下限对I.I.D。在二进制对称通道上的合奏以及用于无内存通道上的恒定组件代码。我们的结果同时恢复为特殊情况，并且对任意字母，任意通道（例如具有内存的有限状态通道）和任意成对独立的合奏仍然有效。我们将结果专注于I.I.D.，在离散的无内存通道上的恒定组合和成本约束的合奏以及在有限状态通道上的合奏。
This paper shows that the probability that the error exponent of a given code randomly generated from a pairwise independent ensemble being smaller than a lower bound on the typical random-coding exponent tends to zero as the codeword length tends to infinity. This lower bound is known to be tight for i.i.d. ensembles over the binary symmetric channel and for constant-composition codes over memoryless channels. Our results recover both as special cases and remain valid for arbitrary alphabets, arbitrary channels -- for example finite-state channels with memory -- and arbitrary pairwise-independent ensembles. We specialize our results to the i.i.d., constant-composition and cost-constrained ensembles over discrete memoryless channels and to ensembles over finite-state channels.
