Collaborative Research: Energy-Efficient Cognitive Networking

合作研究：节能认知网络

• 批准号: 1147730
• 负责人: Anthony Ephremides
• 金额: $ 17.29万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1147730&HistoricalAwards=false
• 关键词: Collaborative; Research; Energy; Efficient; Cognitive

This project addresses two of the grand challenges of the next decade: green wireless communication systems and spectrum efficiency, through a collaborative research and education plan utilizing optimization theory, and involving researchers from the U.S. and Finland. This project considers energy efficiency for cognitive radio networks and introduces a novel optimization-based methodology. It builds on existing results to establish a new focus on green cognitive networking. The way in which energy is consumed in cognitive networks provides unique opportunities for exploiting the cognitive process to save energy and for using energy reduction techniques to modify and improve the performance of cognitive networks. A unique feature of this project is the introduction of an optimization-based methodology for establishing and attaining ultimate performance limits. In this project, PIs develop energy performance bounds that yield insights for design of general networks, derive optimal tradeoffs between fundamental performance criteria, use optimization formulations for establishing and achieving ultimate performance limits, and design protocols that are optimal in the presence of temporal cognitive systems evolution. Research results of this work will be widely promulgated through the usual means of publication and dissemination and will have significant impact on energy efficiency of spectrum-efficient wireless systems.

该项目通过采用优化理论的协作研究和教育计划，解决了未来十年的两个巨大挑战：绿色无线通信系统和光谱效率，并参与了美国和芬兰的研究人员。该项目考虑了认知无线网络的能源效率，并引入了一种基于优化的方法。它以现有结果为基础，以建立对绿色认知网络的新关注。认知网络中消耗能量的方式为利用认知过程提供了独特的机会，以节省能量并使用减少能量技术来修改和改善认知网络的性能。该项目的一个独特功能是引入基于优化的方法来建立和达到最终性能限制。在该项目中，PI开发了能源绩效界限，从而产生一般网络设计的见解，在基本绩效标准之间获得最佳的权衡，使用优化公式来建立和实现最终的性能限制，以及在存在时间认知系统进化的情况下最佳的设计协议。这项工作的研究结果将通过通常的出版和传播方式广泛颁布，并将对频谱有效的无线系统的能源效率产生重大影响。