论文标题
错误指数与典型SLEPIAN-WOLF代码的过度速率指数之间的权衡取舍
Trade-offs Between Error Exponents and Excess-Rate Exponents of Typical Slepian-Wolf Codes
论文作者
论文摘要
典型的随机代码（TRC）在源代码编码的通信方案中使用解码器的侧面信息是这项工作的主要主题。我们研究了半确定性代码合奏，这是普通随机代码合奏的某些变体。在此代码集合中，将源的相对较小类型的类以一对一的方式确定性地分配到可用的垃圾箱中。结果，误差概率急剧下降。在少数重要的特殊情况下，得出了TRC的随机归因误差指数和TRC的误差指数。我们表明，某些通用解码器（例如，具有经验熵度量的随机可能解码器）也可以实现最佳解码下的性能。此外，我们讨论了典型的随机半决赛代码的误差指数与超级率指数之间的权衡，并表征其最佳速率函数。我们表明，对于任何一对相关的信息源，当区块长度趋于无穷大时，误差和过剩率概率都会成倍消失。
Typical random codes (TRC) in a communication scenario of source coding with side information at the decoder is the main subject of this work. We study the semi-deterministic code ensemble, which is a certain variant of the ordinary random binning code ensemble. In this code ensemble, the relatively small type classes of the source are deterministically partitioned into the available bins in a one-to-one manner. As a consequence, the error probability decreases dramatically. The random binning error exponent and the error exponent of the TRC are derived and proved to be equal to one another in a few important special cases. We show that the performance under optimal decoding can be attained also by certain universal decoders, e.g., the stochastic likelihood decoder with an empirical entropy metric. Moreover, we discuss the trade-offs between the error exponent and the excess-rate exponent for the typical random semi-deterministic code and characterize its optimal rate function. We show that for any pair of correlated information sources, both error and excess-rate probabilities are exponentially vanishing when the blocklength tends to infinity.
