Derpich Milan S, Østergaard Jan
Department of Electronic Engineering, Universidad Técnica Federico Santa María, Av. España 1680, Valparaíso 2390123, Chile.
Department of Electronic Systems, Aalborg University, 9220 Aalborg, Denmark.
Entropy (Basel). 2021 Apr 26;23(5):533. doi: 10.3390/e23050533.
We present novel data-processing inequalities relating the mutual information and the directed information in systems with feedback. The internal deterministic blocks within such systems are restricted only to be causal mappings, but are allowed to be non-linear and time varying, and randomized by their own external random input, can yield any stochastic mapping. These randomized blocks can for example represent source encoders, decoders, or even communication channels. Moreover, the involved signals can be arbitrarily distributed. Our first main result relates mutual and directed information and can be interpreted as a law of conservation of information flow. Our second main result is a pair of data-processing inequalities (one the conditional version of the other) between nested pairs of random sequences entirely within the closed loop. Our third main result introduces and characterizes the notion of in-the-loop (ITL) transmission rate for channel coding scenarios in which the messages are internal to the loop. Interestingly, in this case the conventional notions of transmission rate associated with the entropy of the messages and of channel capacity based on maximizing the mutual information between the messages and the output turn out to be inadequate. Instead, as we show, the ITL transmission rate is the unique notion of rate for which a channel code attains zero error probability if and only if such an ITL rate does not exceed the corresponding directed information rate from messages to decoded messages. We apply our data-processing inequalities to show that the supremum of achievable (in the usual channel coding sense) ITL transmission rates is upper bounded by the supremum of the directed information rate across the communication channel. Moreover, we present an example in which this upper bound is attained. Finally, we further illustrate the applicability of our results by discussing how they make possible the generalization of two fundamental inequalities known in networked control literature.
我们提出了与具有反馈的系统中的互信息和有向信息相关的新颖数据处理不等式。此类系统中的内部确定性模块仅被限制为因果映射,但允许是非线性且时变的,并且通过其自身的外部随机输入进行随机化,从而可以产生任何随机映射。这些随机模块例如可以表示源编码器、解码器,甚至通信信道。此外,所涉及的信号可以是任意分布的。我们的第一个主要结果涉及互信息和有向信息,可以解释为信息流守恒定律。我们的第二个主要结果是关于完全在闭环内的嵌套随机序列对之间的一对数据处理不等式(其中一个是另一个的条件版本)。我们的第三个主要结果引入并刻画了用于信道编码场景的环路内(ITL)传输速率的概念,其中消息在环路内部。有趣的是,在这种情况下,与消息熵相关的传统传输速率概念以及基于最大化消息与输出之间互信息的信道容量概念被证明是不充分的。相反,正如我们所展示的,ITL传输速率是这样一种唯一的速率概念:当且仅当这种ITL速率不超过从消息到解码消息的相应有向信息速率时,信道编码才能达到零错误概率。我们应用我们的数据处理不等式来表明,可实现的(在通常的信道编码意义上)ITL传输速率的上界由通信信道上有向信息速率的上界给出。此外,我们给出了一个达到此上界的例子。最后,我们通过讨论这些结果如何使得网络化控制文献中已知的两个基本不等式的推广成为可能,进一步说明了我们结果的适用性。