CIF: Small: Limitations of communication and control and over noisy feedback links

通信网络的广泛可用性促进了节点之间的交互，这些节点通过在可用的通信链路上交换信息而不断地相互影响。从社交网络到生物网络，这种动态的、交互式的交流方式在许多网络系统中都很常见。它的因果性质不同于经典通信系统的批编码和处理，传统的信息论结果不能很好地处理。这些设置是更合适的运作和理解的控制和监管过程，更普遍的是，过程的学习和adaptation.The建议的研究的主要目标是表征的基本限制，相互作用的动态系统在嘈杂的通信链路。 我们开始分析问题的交互式点到点通信的编码器有机会从接收器的噪声反馈的基础上一个新的信息理论量，捕获的实际信息流在前向信道时，反馈信道是嘈杂的。从它，我们建议推导出可计算的界限上的噪声反馈能力的公共信道，开发控制启发的实际编码方案，是强大的反馈链路中的噪声，并使用噪声反馈的成本和效益的特点。 此外，我们提出了扩展的理论，以其他新的嘈杂的反馈结构的远程指导和虚拟现实应用的动机。由此产生的动力系统同时是通信和控制系统。我们的目标是研究这些相互作用的动态系统的性能和局限性，在一个综合的方式，通过扩展网络控制系统的相关结果。

The widespread availability of communication networks fosters interactions among nodes that constantly affect each other by exchanging information over the available communication links. This dynamic, interactive, aspect of communication is common to many networked systems, from social networks to biological networks. Its causal nature differs from the batch coding and processing of classical communication systems and is not handled well by the traditional information theory results. These settings are more appropriate for the functioning and the understanding of control and regulation processes and, more generally, processes of learning and adaptation.The main objective of the proposed research is to characterize the fundamental limitations of interacting dynamical systems over noisy communication links. We start analyzing the problem of interactive point-to-point communication where the encoder has access to noisy feedback from the receiver based on a new information theoretic quantity that captures the actual information flow in the forward channel when the feedback channel is noisy. From it, we propose to derive computable bounds on the noisy feedback capacity for common channels, to develop control-inspired practical coding schemes that are robust to noise in the feedback link, and to characterize costs and benefits of using noisy feedback. Further, we propose extensions of the theory to other new noisy feedback structures motivated by remote guidance and virtual reality applications. The resulting dynamical systems are both communication and control systems at the same time. We aim to study properties and limitations of these interacting dynamical systems, in an integrated way, by extending the relevant results in networked control systems.