Coding for Networked Control Systems over Lossy Links

未来十年将见证具有无线通信能力的设备数量的爆炸性增长，这些设备可以以自组织和/或集中的方式感知、测量、驱动、交互和彼此通信。这样的设备将出现在汽车、家用电器、可穿戴电子产品、传感器网络、监控系统、各种控制器和许多其他领域。对于这些新兴设备，一个常见的笼统说法是物联网。如此众多的智能设备带来的巨大机遇之一是，它们可以合作、协调、共同决策，并通过采取联合行动来影响所处的环境。实现这一机会的一个主要挑战是，这些多个设备或代理必须以分散的方式完成，同时通过不可靠的链路进行通信。虽然通信系统总是不得不处理不可靠的链路，但由于需要交换的控制和侦听信号的实时特性、动态变化的业务模式以及代理的可能移动性，为通信系统设计的传统方案不再适用。这项提案的目标是促进联网系统的设计和分析，这些系统通过嘈杂的通信链路相互作用和通信，并建立在调查人员的基础上。先前的工作是构造第一个高效可解码的树码，其可用于在有损擦除链路上可靠地实现任何分布式协议。如何更好地在有损链路网络上操作分布式异质代理是一个活跃的研究领域。问题包括代理商应该交换哪些信息？他们应该如何最好地对其测量或控制信号进行量化和编码，以对抗网络中的不确定性(延迟或消息丢弃)？他们如何促进合作，战胜竞争？他们怎么能以一种分布式的方式完成这一切呢？诸若此类。这些极具挑战性的问题与通信、网络和控制等传统领域重叠，并以新颖的方式将各自的要素结合在一起。因此，一种能够以整体方式处理这些问题的理论尚未出现。该建议试图通过研究树形编码以及通过研究因果信源编码来开始这样的理论，树形编码是一种新的编码范例，允许在有损链路上可靠地实施交互协议。树形码是近二十年前作为信息论和控制之间的桥梁而引入的，但由于不存在具有有效译码的显式结构，因此并未获得太大的吸引力。因果源代码编码这一领域的研究就更少了。研究的主要内容包括：(1)针对AWGN和BSC等其他类型的信道设计可高效编码和可译码的树形编码；(2)研究控制系统的性能以及信源编码、信道编码和控制器设计之间的相互作用和权衡；(3)研究因果信源编码，特别是因果变换编码及其在控制环境下如何优化；(4)在删除链路上实现分布式协议；(5)从控制理论确定度量以指导编码设计。

The coming decade will witness an explosive growth in the number of devices with wireless communication capabilities and that can sense, measure, actuate, interact, and communicate with each other in ad hoc and/or centralized fashions. Such devices will appear in automobiles, household appliances, wearable electronics, sensor networks, surveillance systems, various controllers and many others. A common catch-all phrase for these emerging devices is the Internet-of-Things. One of the great opportunities that such a plethora of intelligent devices presents is that they can cooperate, coordinate, make joint decisions, and influence the environment they are in by taking joint actions. A main challenge in realizing this opportunity is that these multiple devices, or agents, must do so in a decentralized way and while communicating over unreliable links. Although communication systems have always had to deal with unreliable links, because of the real-time nature of the control and sensing signals that need to be exchanged, the dynamically-changing traffic patterns, and the possible mobility of the agents, traditional schemes designed for communication systems are no longer applicable. The goal of this proposal is to facilitate the design and analysis of networked systems that interact and communicate with each other over noisy communication links and builds on the investigators? prior work of constructing the first efficiently decodable tree codes that can be used to reliably implement any distributed protocol over lossy erasure links. How best to operate distributed heterogeneous agents over networks of lossy links is an area of active research. Questions include what information should the agents exchange? How best should they quantize and encode their measurements or control signals to combat the uncertainties (delay or message drops) in the network? How can they facilitate cooperation and overcome the competition? How can they do all this in a distributed fashion? And so on. These very challenging questions overlap with the conventional fields of communications, networking and control and combine elements of each in novel ways. As result, a theory that can deal with them in a holistic manner has yet to emerge. This proposal attempts the beginning of such a theory through the study of tree codes, a new paradigm in coding that allows the reliable implementation of interactive protocols over lossy links, as well as through the study of causal source coding. Tree codes were introduced nearly twenty years ago as a bridge between information theory and control, but did not gain much traction since explicit constructions with efficient decoding did not exist. The area of causal source coding is even less explored. The proposed research has five main thrusts: (1) the design of efficiently encodable and decodable tree codes for other classes of channels, such as AWGN and BSC, (2) the study of the performance of control systems and the interaction and tradeoffs between source coding, channel coding and controller design, (3) the study of causal source coding; in particular, causal transform codes and how they can be optimized in the control setting, (4) implementing distributed protocols over erasure links, and (5) determining metrics from control theory to guide the code design.