EARS: Enhancing Radio-Frequency Spectrum Through Interference Resilient Cognitive Radio Systems: Design, Performance Analysis and Optimization

EARS：通过抗干扰认知无线电系统增强射频频谱：设计、性能分析和优化

• 批准号: 1547447
• 负责人: Krishna Narayanan
• 金额: $ 40.73万
• 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: 2015
• 资助国家: 美国
• 起止时间: 2015-10-01 至 2019-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1547447&HistoricalAwards=false
• 关键词: EARS; Enhancing; Radio; Frequency; Spectrum

The continuous increase in the number of wireless devices and sensors along with the huge demand for higher data rates and limited radio frequency spectrum resources have prompted the need for novel wireless communications technologies with improved radio frequency spectrum sharing features. Recent radio spectrum measurements have corroborated the fact that the radio spectrum is being used inefficiently; and consequently, the concept of cognitive radio has been proposed as a promising approach for the efficient utilization of the radio frequency spectrum. A cognitive radio represents a communication system equipped with the abilities to learn its surrounding environment through sensing and measurements and to adapt its features for a better utilization of existing radio frequency spectrum resources with the aim of securing communications links with adequate quality of service. This proposal addresses several important problems that must be overcome before cognitive radio systems can be implemented in practice. These challenges include the design of circuits with adequate precision for processing of the received signals, the design of fast and computationally efficient ways to sense the occupancy of the spectrum and the design and analysis of multiple access schemes that will permit many users to share the spectrum without causing undue interference to each other. This project will use innovative techniques to solve these challenges thereby enabling a better utilization of the available radio spectrum resources. Applications of the proposed work include radio astronomy, communication networks, smart grids, wireless sensing and monitoring devices, remote monitoring of earth, and telemedicine.This project will design interference-resilient orthogonal frequency division multiplexing based cognitive networks and optimize their performance for better utilization of the radio frequency spectrum. The objective is to develop transformative solutions and approaches by unveiling and exploiting cross-disciplinary concepts and results from mixed analog/digital signal processing, fast spectrum sensing, computational statistics and stochastic geometry with significant impact to both theory and practice. Successful completion of this project holds the potential to advance the state-of-the-art knowledge and understanding in the deployment and optimization of spectrum sharing communications networks. This project will develop new algorithms and methodologies to optimize the design of a radio frequency front-end and analog-to-digital converters in the presence of primary user interference, and multiple-access schemes to mitigate secondary user interference. This project will also contribute to the development of large-scale simulation and computational methods for enhancing the operation of cognitive wireless communications networks. The proposed research work will be integrated with the educational mission through the development of innovative pedagogical practices, advising of students, active recruitment of domestic students and students from under-represented groups. These efforts will dovetail with the ambitious 25 by 25 growth plan at Texas A&M University, which seeks to increase the enrollment in the College of Engineering to 25,000 students by 2025, thereby increasing access to high quality education.

无线设备和传感器数量的不断增加，以及对更高数据速率的巨大需求和有限的射频频谱资源，促使人们需要具有改进的射频频谱共享功能的新型无线通信技术。最近的无线电频谱测量证实了无线电频谱使用效率低下的事实；因此，认知无线电的概念被提出作为有效利用无线电频谱的一种有前途的方法。认知无线电代表一种通信系统，能够通过感测和测量来了解周围环境，并调整其功能以更好地利用现有射频频谱资源，从而确保通信链路具有足够的服务质量。该提案解决了认知无线电系统在实践中实施之前必须克服的几个重要问题。这些挑战包括设计具有足够精度的电路来处理接收到的信号、设计快速且计算高效的方法来感知频谱的占用情况以及允许许多用户共享频谱的多址方案的设计和分析而不会对彼此造成不当干扰。该项目将使用创新技术来解决这些挑战，从而更好地利用可用的无线电频谱资源。拟议工作的应用包括射电天文学、通信网络、智能电网、无线传感和监测设备、地球远程监测和远程医疗。该项目将设计基于抗干扰正交频分复用的认知网络，并优化其性能以更好地利用无线电频谱。其目标是通过揭示和利用混合模拟/数字信号处理、快速频谱传感、计算统计和随机几何的跨学科概念和结果来开发变革性解决方案和方法，对理论和实践产生重大影响。该项目的成功完成有望促进频谱共享通信网络部署和优化方面的最先进知识和理解。该项目将开发新的算法和方法，以在存在主要用户干扰的情况下优化射频前端和模数转换器的设计，并开发多址方案以减轻次要用户干扰。该项目还将有助于开发大规模模拟和计算方法，以增强认知无线通信网络的运行。拟议的研究工作将通过发展创新的教学实践、为学生提供建议、积极招募国内学生和代表性不足群体的学生，与教育使命相结合。这些努力将与德克萨斯 A&M 大学雄心勃勃的 25 x 25 增长计划相吻合，该计划旨在到 2025 年将工程学院的招生人数增加到 25,000 名学生，从而增加获得高质量教育的机会。