EARS: Collaborative Research: Intelligence Measure of Cognitive Radio Networks

EARS：协作研究：认知无线电网络的智能测量

• 批准号: 1464487
• 负责人: Kai Zeng
• 金额: $ 22.51万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-15 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1464487&HistoricalAwards=false
• 关键词: EARS; Collaborative; Research; Intelligence; Measure

Research on spectrum sharing has generated a large amount of spectrum measurement data and many spectrum sharing techniques. Most of the techniques are based on cognitive radio networks (CRNs) because the cognition capability is necessary for optimizing spectrum efficiency and guaranteeing safe coexistence in the presence of the spectrum uncertainty. Such cognitive capabilities collectively defines the intelligence of CRNs. Although cognition and intelligence are vital for CRNs, their quantitative specification is largely open. This project addresses this open question by developing a framework for investigating quantitatively the cognitive capabilities and the intelligence of CRNs. This project develops both a theoretical approach and an empirical approach to construct a CRN intelligence model. This model is inspired from the Cattell-Horn-Carroll human intelligence model. On the other hand, the pioneering theoretical approach is in sharp contrast to conventional human intelligence research that is mainly empirical. In addition, this project develops a CRN testing battery to measure the intelligence as CRN IQ (intelligence quotient) following psychometric practices. Finally, this project initiates innovative research in IQ-based multi-hop routing and IQ-based immunity to Denial-of-Service attacks, where innovative CRN techniques are developed with the aim of enhancing important cognitive capabilities. This project adopts a big data approach to exploit the vast amount of existing spectrum measurement data and CRN research results. Psychometric techniques are exploited to resolve challenges involved in this big data application.This project impacts society by expediting the commercial success of spectrum sharing technology. It integrates three traditionally disparate areas: wireless communications, psychology, and big data. The framework for constructing intelligence measure is useful to many other systems such as cognitive computing, cognitive control and cognitive radar. This project enhances the value of the spectrum measurement data and leads to a new direction for big data utilization. This project impacts education in many aspects, such as stimulating student research via the human intelligence analogy, supporting hands-on curriculum with the CRN testing battery, setting up CRN IQ competition projects, and outreaching to under-represented students and high school students.This project impacts society by expediting the commercial success of spectrum sharing technology. It integrates three traditionally disparate areas: wireless communications, psychology, and big data. The framework for constructing intelligence measure is useful to many other systems such as cognitive computing, cognitive control and cognitive radar. This project enhances the value of the spectrum measurement data and leads to a new direction for big data utilization. This project impacts education in many aspects, such as stimulating student research via the human intelligence analogy, supporting hands-on curriculum with the CRN testing battery, setting up CRN IQ competition projects, and outreaching to under-represented students and high school students.

频谱共享的研究产生了大量的频谱测量数据和多种频谱共享技术。大多数的技术是基于认知无线电网络（CRN），因为认知能力是必要的，以优化频谱效率，并保证安全共存的频谱不确定性的存在。这些认知能力共同定义了CRN的智能。尽管认知和智能对于CRN至关重要，但它们的定量规范在很大程度上是开放的。该项目通过开发一个定量调查CRN的认知能力和智能的框架来解决这个悬而未决的问题。本研究以理论与实证相结合的方法建构一个CRN智能模型。该模型的灵感来自于Cattell-Horn-卡罗尔的人类智能模型。另一方面，开创性的理论方法与传统的主要是经验主义的人类智力研究形成鲜明对比。此外，本研究亦发展一套CRN测验组合，以测量智力，即CRN IQ（智商）。最后，该项目启动了基于IQ的多跳路由和基于IQ的拒绝服务攻击免疫力的创新研究，其中创新的CRN技术的开发旨在提高重要的认知能力。该项目采用大数据方法，利用现有的大量频谱测量数据和CRN研究成果。心理测量技术被用来解决这个大数据应用所涉及的挑战。这个项目通过加速频谱共享技术的商业成功来影响社会。它整合了三个传统上完全不同的领域：无线通信、心理学和大数据。该智能测度的构造框架对认知计算、认知控制、认知雷达等系统也有一定的借鉴意义。该项目提高了频谱测量数据的价值，为大数据的利用开辟了新的方向。 该项目在多个方面对教育产生影响，例如通过人类智能类比激发学生研究，通过CRN测试电池支持实践课程，设立CRN IQ竞赛项目，以及向代表性不足的学生和高中生进行宣传。该项目通过加速频谱共享技术的商业成功来影响社会。它整合了三个传统上完全不同的领域：无线通信、心理学和大数据。该智能测度的构造框架对认知计算、认知控制、认知雷达等系统也有一定的借鉴意义。该项目提高了频谱测量数据的价值，为大数据的利用开辟了新的方向。 该项目在许多方面影响教育，例如通过人类智力类比刺激学生研究，用CRN测试电池支持实践课程，建立CRN智商竞赛项目，以及向代表性不足的学生和高中生推广。