EAGER: Cognitive Radio with 2-D Cognition: Dynamic Spectrum vs. Power Accesses

EAGER：具有 2D 认知功能的认知无线电：动态频谱与电源接入

• 批准号: 1265227
• 负责人: Shuguang Cui
• 金额: $ 30万
• 依托单位: Texas A&M Engineering Experiment Station
• 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: 2013-02-01 至 2016-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1265227&HistoricalAwards=false
• 关键词: EAGER; Cognitive; Radio; Cognition; Dynamic

This project focuses on the fundamental tradeoff between spectrum efficiency and energy efficiency in cognitive radio systems by exploring the correlations across both spectrum and energy domains, in the notions of both frequency holes and energy holes. The considered application scenario is a spectrum sharing system with both legacy and cognitive radios, where the nodes are powered by either smart grids or environment energy harvesters or a mix of two. The three main research objectives are: develop joint 2-D sensing scheme to explore the correlation between frequency holes and energy holes; derive efficiency maximizing resource allocation schemes considering constraints in both energy and spectrum domains; and study performance enhancement mechanisms in the framework of collaborative clouds via node conferencing. Novel interdisciplinary approaches are applied to combine the methods of 2-D statistical signal processing, non-convex optimization, and analytical energy harvesting system modeling to study the unique problem considered for the newly defined cognitive radio systems with 2-D cognition. The project provides both theories and algorithms for energy-efficient operation of future cognitive radio systems with accesses to both spectrum and energy dynamics. The research findings will be incorporated into graduate courses; the results will be disseminated to the community via journal papers and conference presentations.

该项目的重点是在认知无线电系统的频谱效率和能源效率之间的基本权衡，通过探索跨频谱和能源领域的相关性，在频率洞和能源洞的概念。所考虑的应用场景是具有传统无线电和认知无线电的频谱共享系统，其中节点由智能电网或环境能量收集器或两者的混合供电。三个主要的研究目标是：开发联合2-D传感方案，探索频率洞和能量洞之间的相关性;推导效率最大化的资源分配方案，考虑在能量和频谱域的约束;和研究性能增强机制的框架下，通过节点会议的协作云。新的跨学科的方法被应用到联合收割机相结合的方法，2-D统计信号处理，非凸优化，和分析能量收集系统建模研究的独特问题，考虑新定义的认知无线电系统与2-D认知。该项目为未来认知无线电系统的节能操作提供了理论和算法，可同时访问频谱和能量动态。研究结果将纳入研究生课程;研究结果将通过期刊论文和会议报告向社会传播。