EAGER:SC2: Collaborative Intelligent Radio Network Design For Cooperative Spectrum Sharing

EAGER:SC2：用于协作频谱共享的协作智能无线电网络设计

• 批准号: 1737934
• 负责人: Biao Chen
• 金额: $ 10万
• 依托单位: Syracuse University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-01 至 2019-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1737934&HistoricalAwards=false
• 关键词: EAGER; SC2; Collaborative; Intelligent; Radio

The proliferation of wireless devices and services presents an acute demand on the radio frequency spectrum. The so-called spectrum scarcity has led to numerous initiatives spearheaded by the Federal Communications Commission to advance how frequency spectrum should be allocated and utilized. This project is a complex, inter-disciplinary effort to address effective sharing of spectrum. The effort involves both graduate and undergraduate students from a diverse background; participation in this project will provide the students a unique and invaluable experience and will help cultivate their long term interest in STEM related areas.The project will develop a robust and run-time adaptive radio network with built-in machine intelligence that is able to co-exist with other unknown radio networks in the absence of any spectrum pre-planning. A thoroughly tested software radio network will be developed to ensure that various high level learning and networking functions will be integrated seamlessly to attain the design objectives. Three computing platforms (CPU Server, FPGA, and GPU) will be utilized in an optimal manner by taking into account various computing bandwidth and latency constraints to accommodate the various computing/learning functions. The collective development of the collaboration protocol will help identify the most critical information necessary in facilitating efficient spectrum usage among independent users.

无线设备和服务的激增对无线电频谱提出了迫切的需求。所谓的频谱稀缺导致了由联邦通信委员会牵头的许多倡议，以推进频谱的分配和利用。该项目是一项复杂的跨学科工作，旨在解决频谱的有效共享问题。该项目涉及来自不同背景的研究生和本科生;参与该项目将为学生提供独特而宝贵的经验，并有助于培养他们对STEM相关领域的长期兴趣。该项目将开发一个强大的运行时自适应无线电网络，内置机器智能，能够在没有任何频谱预先规划的情况下与其他未知的无线电网络共存。将开发一个经过全面测试的软件无线电网络，以确保各种高级学习和网络功能无缝集成，以实现设计目标。三个计算平台（CPU服务器、FPGA和GPU）将通过考虑各种计算带宽和延迟约束以最佳方式使用，以适应各种计算/学习功能。合作协议的集体开发将有助于确定促进独立用户之间有效使用频谱所需的最关键信息。