CAREER: Information-Scaling Laws, ``Bit-conservation'' Principles, and Robust Coding Architectures in Sensor Networks

基于构建下一代基于视频的传感器网络的愿景，该网络能够使用低分辨率无线摄像机的大型分布式网络进行实时“超分辨率成像”，该项目引入了分布式采样和视频编码的新范例，这些范例位于信号处理和网络信息理论的前沿。该项目开发的新的数据采集、压缩和推理方法预计将影响大规模无线传感器网络的架构和发展，并在需要主动监测遥测数据的应用中推进最先进的技术，如监视、国土安全、智能交通和环境监测。本项目1)利用非调和傅立叶分析、抖动采样、2)开发新的实时分布式视频编码架构，该架构可适应处理复杂性和传感分辨率的灵活分布，并且对信息丢失和相关不确定性具有鲁棒性。引入了一种新的“位守恒”原理来描述分布式采样中传感器精度和传感器密度之间的权衡。研究工作还辅以一项教育工作，通过1)课程开发，培训年轻工程师，使他们在分布式信息系统的设计和开发方面变得熟练，其中一门关于分布式信息处理和通信的新课程强调原始研究和项目开发；2)编写一个引人注目的玩具研究难题语料库，说明分布式信号处理和网络信息理论的基本概念，并整合到本科和研究生课程中；3)创建一个新的介绍分布式信号处理中的信息理论的研究生水平的教科书。

With a vision for architecting the next generation video-based sensor networks capable of real-time ``superresolution imaging'' using a large distributed network of poor-resolution wireless cameras, thisproject introduces new paradigms for distributed sampling and video coding that lie in the frontier of signal processing and network information theory. The new data-acquisition, compression, and inference methods developed in this project are expected to influence the architecture and evolution of large-scale wireless sensor networks and advance the state-of-the-art in applications requiring active monitoring of telemetry data such as surveillance, homeland security, intelligent transportation, and environmental monitoring.This project 1) studies fundamental performance limits and constructive approaches for integrating poor device precision and large-scale deployment with distributed sampling and compression using new results in nonharmonic Fourier analysis, dithered sampling, and Wyner-Ziv coding and 2) develops new real-time distributed video-coding architectures that are amenable to flexible distribution of processing complexity and sensing resolution and are robust to information loss and correlation uncertainty. A novel ``bit-conservation'' principle is introduced for characterizing the tradeoffs between sensor precision and sensor density in distributed sampling. The research effort is complemented by an educational effort to train young engineers to become skilled in the design and development of distributed information systems through 1) curriculumdevelopment, with a new course on distributed information processing and communication having an emphasis on raw-research and project development, 2) the compilation of a corpus of striking toy researchpuzzles illustrating fundamental concepts in distributed signal processing and network information theory integrated into the undergraduate and graduate curricula, and 3) the creation of a new introductory graduate-level text-book on information theory in distributed signal processing.