Stochastic Diffusion, Adaptive Estimation, and Prediction Models for Wireless Networked Systems

无线网络系统的随机扩散、自适应估计和预测模型

• 批准号: 1334094
• 负责人: Seddik Djouadi
• 金额: $ 24万
• 依托单位: University of Tennessee Knoxville
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-01 至 2017-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1334094&HistoricalAwards=false
• 关键词: Stochastic; Diffusion; Adaptive; Estimation; Prediction

The objective of this research is to develop methods for modeling, estimation, and prediction of wireless networks in real time. The modeling approach generalizes to diverse propagation environments including "urban canyons", and directly addresses issues such as the random and ever changing interference effects and noise sources caused by the transmitter population. The research will result in general methods that will improve communication channel utilization and thereby performance of various wireless networked system applications. Deliverable includes fundamental algorithms, modeling and analysis tools, demonstration and validation via simulation and hardware implementation, documentation of research results, and engineering student education.If successful, particular benefits of this research will accrue to networked control systems, such as mobile sensor networks, unmanned vehicles, remote surgery, haptics collaboration, health monitoring, agricultural areas/farms, home networking, and wireless networks multimedia applications. For example, the economically efficient delivery of highly reliable electric power is increasingly dependent on networked SCADA (Supervisory Control and Data Acquisition System) and distributed control systems operating over commercially available, and frequently internet protocol (IP) based communication technologies. The results will be disseminated using different platforms to allow the creation of commercial software and hardware (transceivers) with increased performance, reliability, and reduced wiring costs. The educational plan places a particular emphasis upon the cultivation of a diverse student population and inclusion of under-represented minorities, by utilizing student and mentor teams, incorporating graduate and undergraduate students, and focusing upon project-oriented integrated systems design. A partnership with Oak Ridge National Laboratory will provide realistic data sets and applications, and opportunities for direct feedback from practitioners to the students.

本研究的目的是开发实时建模、估计和预测无线网络的方法。该建模方法可推广到包括“城市峡谷”在内的各种传播环境，并直接解决诸如随机且不断变化的干扰效应以及由发射机群体引起的噪声源等问题。 该研究将产生提高通信信道利用率的通用方法，从而提高各种无线网络系统应用的性能。可交付成果包括基本算法、建模和分析工具、通过模拟和硬件实现进行演示和验证、研究结果记录以及工程学生教育。如果成功，这项研究的特殊好处将为网络控制系统带来好处，例如移动传感器网络、无人驾驶车辆、远程手术、触觉协作、健康监测、农业区/农场、家庭网络和无线网络多媒体应用。 例如，经济高效地提供高度可靠的电力越来越依赖于网络化 SCADA（监控和数据采集系统）和分布式控制系统，这些系统通过商用且通常基于互联网协议 (IP) 的通信技术运行。结果将使用不同的平台进行传播，以允许创建具有更高性能、可靠性并降低布线成本的商业软件和硬件（收发器）。 该教育计划特别强调通过利用学生和导师团队、吸收研究生和本科生以及注重以项目为导向的集成系统设计，培养多元化的学生群体并包容代表性不足的少数群体。与橡树岭国家实验室的合作将提供真实的数据集和应用程序，以及从业者向学生提供直接反馈的机会。