EARS: Accelerating Spectrum Access in Cognitive Radio Networks via Social Analysis of Secondary Users

EARS：通过二级用户的社会分析加速认知无线电网络中的频谱访问

• 批准号: 1343355
• 负责人: Jiang Linda Xie
• 金额: $ 60万
• 依托单位: University of North Carolina at Charlotte
• 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: 2014-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1343355&HistoricalAwards=false
• 关键词: EARS; Accelerating; Spectrum; Access; Cognitive

A fundamental operation for users in cognitive radio networks (CRNs) to access the spectrum is channel rendezvous. After rendezvous is established, channel information exchange and propagation among users are also essential for efficient spectrum access. Existing studies on channel rendezvous in CRNs have limitations and are unsuitable for efficient access scenarios. Additional information about users can help generate intelligent designs in CRNs that can shorten spectrum access delay. However, due to practical constraints, such information is extremely difficult to obtain before rendezvous is established. Mining the social patterns of CR users (or secondary users, SUs) and intelligently utilizing the captured social information is a promising approach. The objective of this project is to design, analyze, and evaluate fast and efficient spectrum access schemes for CRNs without a common control channel. One unique feature of this work is the consideration of SU social patterns and the incorporation of social analysis to enhance spectrum access efficiency. The approach involves analyzing the time, location, and spectrum-dependent social patterns of SUs; identifying and addressing new challenges in channel rendezvous, security, and recommendation designs with the assistance of SU social analysis; and proactively utilizing social patterns of SUs for fully distributed fast and secure spectrum access design. This project will have a significant impact on efficient spectrum access. Social analysis of users is a critical component to further enhance spectrum access efficiency and accelerate CRN deployment. This interdisciplinary research is potentially transformative as it will help generate innovative techniques to numerous CRN applications. It will also greatly enhance the understanding of social interactions of mobile users in wireless networks. This project provides an excellent opportunity for graduate and undergraduate research students to gain valuable educational training and research experiences. The research results will be presented at IEEE/ACM journals and international conferences.

访问频谱的认知无线网络（CRN）中用户的基本操作是频道会合。建立会合后，用户之间的渠道信息交换和传播对于有效的频谱访问也至关重要。现有关于CRN中通道会合的研究有局限性，不适合有效的访问方案。有关用户的其他信息可以帮助在CRN中生成智能设计，以缩短光谱访问延迟。但是，由于实用的限制，在建立会合之前很难获得此类信息。挖掘CR用户（或二级用户，SUS）的社交模式并智能利用被捕获的社交信息是一种有前途的方法。该项目的目的是设计，分析和评估没有共同控制通道的CRN的快速有效频谱访问方案。这项工作的一个独特特征是考虑SU社会模式以及纳入社会分析以提高频谱访问效率。该方法涉及分析SUS的时间，位置和依赖频谱的社会模式；在SU社会分析的帮助下，在渠道会合，安全和建议设计中确定并解决新的挑战；并主动利用SUS的社会模式进行全面分布的快速和安全频谱访问设计。该项目将对有效的光谱访问产生重大影响。用户的社会分析是进一步提高光谱访问效率并加速CRN部署的关键组成部分。这项跨学科研究具有可能性的变革性，因为它将有助于为众多CRN应用产生创新技术。它还将大大增强对无线网络中移动用户的社交互动的理解。该项目为研究生和本科研究专业的学生提供了一个绝佳的机会，可以获得宝贵的教育培训和研究经验。研究结果将在IEEE/ACM期刊和国际会议上介绍。