Collaborative Research: Collaborative Quickest Detection in Ad hoc Networks with Application in Cognitive Radio

协作研究：自组织网络中的协作最快检测及其在认知无线电中的应用

• 批准号: 0830462
• 负责人: Huaiyu Dai
• 金额: $ 9.33万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0830462&HistoricalAwards=false
• 关键词: Collaborative; Research; Quickest; Detection; Ad

Quickest detection is an important technique to detect the change of probability distribution in a random process being monitored. It is widely used in problems like financial decision making, environmental monitoring and industrial quality control. With the rapid development of networking techniques, there exist pressing demands to carry out quickest detection based on observations from many nodes and make decision at more than one node. Motivated by this demand, this research studies collaborative quickest detection in ad hoc networks, in which nodes exchange observation statistics and make local decisions about distribution change. In contrast to existing theory of decentralized quickest detection, the collaborative quickest detection does not need a data processing center, thus avoiding the round-trip time overhead and possible data congestion. Moreover, collaboration can enhance the agility and robustness of the detection of change. The research involves aspects of statistical signal processing (e.g. detection rule), information theory (e.g. source coding) and networking (e.g. scheduling or broadcast). An important application of collaborative quickest detection is spectrum sensing in cognitive radio systems. In such a system, secondary nodes need to monitor the activity of primary users and should quit the frequency band once primary users emerge. It is essentially a problem of quickest detection since the secondary nodes need to detect the change as quickly as possible. Therefore, this research also involves the design of collaborative quickest detection in cognitive radio networks. Inter-disciplinary essence of the research also lends itself to cross-disciplinary education. A one-semester graduate level course will be devised, which introduces quickest detection, cooperative communication and cognitive radio. This project also expects to attract traditionally underrepresented groups.

最快检测是检测被监测随机过程中概率分布变化的一种重要技术。它广泛应用于财务决策、环境监测和工业质量控制等问题。随着网络技术的迅速发展，迫切需要在多个节点上进行基于多个节点观测的快速检测和决策。基于此需求，本研究研究在ad hoc网络中，节点交换观测统计信息，并对分布变化做出局部决策的协作最快检测。与现有的分散式最快检测理论相比，协同式最快检测不需要数据处理中心，从而避免了往返时间开销和可能的数据拥塞。此外，协作可以增强变化检测的灵活性和鲁棒性。研究涉及统计信号处理（如检测规则）、信息论（如信源编码）和网络（如调度或广播）等方面。协作最快检测的一个重要应用是认知无线电系统中的频谱感知。在这样的系统中，次节点需要监视主用户的活动，并且一旦主用户出现就应该退出频带。它本质上是一个最快检测的问题，因为辅助节点需要尽可能快地检测到变化。因此，本研究也涉及认知无线电网络中协同最快检测的设计。研究的跨学科本质也适用于跨学科教育。将设计一个为期一学期的研究生水平的课程，介绍最快检测，合作通信和认知无线电。该项目还有望吸引传统上代表性不足的群体。