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.
翻译:在解码器使用侧边信息进行源代码编码的通信假设中,典型随机代码(TRC)是这项工作的主要主题。我们研究了半确定性代码共和体,这是普通随机宾客代码共和体的某种变体。在这个编码中,源的相对小类以一对一的方式被确定分解到可用的文件夹中。结果,误差概率急剧下降。在少数重要的特殊案例中,TRC随机的错差推介和错推介被推导出来并被证明是等同的。我们表明,某些通用解码器也可以达到在最佳解码中的最佳性能,例如,与实验性昆虫测量仪相匹配的可能性解码。此外,我们讨论误差率与超率偏差之间的利差,以典型的随机半确定性代码为准,并描述其最佳速率功能。我们显示,对于任何对应的信息源而言,在恒定时,误差和超常态的易变等值是恒度。