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.

在认知无线网络（crn）中，用户获取频谱的一个基本操作是信道交会。交会建立后，用户间的信道信息交换和传播也是实现高效频谱接入的关键。现有的crn信道交会研究存在局限性，不适用于高效接入场景。有关用户的其他信息可以帮助在crn中生成智能设计，从而缩短频谱访问延迟。但是，由于实际的限制，在确定会合地点之前，很难获得这种情报。挖掘CR用户（或辅助用户，su）的社交模式并智能地利用捕获的社交信息是一种很有前途的方法。该项目的目标是设计、分析和评估没有公共控制信道的crn快速有效的频谱接入方案。这项工作的一个独特之处在于考虑了SU社会模式并结合了社会分析来提高频谱接入效率。该方法包括分析SUs的时间、位置和依赖于频谱的社会模式；在SU社会分析的帮助下，识别并解决渠道交会、安全性和推荐设计方面的新挑战；主动利用单节点的社交模式进行全分布式、快速、安全的频谱接入设计。该项目将对有效的频谱接入产生重大影响。用户社交分析是进一步提高频谱接入效率、加快CRN部署的重要组成部分。这项跨学科研究具有潜在的变革性，因为它将有助于为众多CRN应用产生创新技术。它还将极大地增强对移动用户在无线网络中的社交互动的理解。该项目为研究生和本科生提供了一个获得宝贵的教育培训和研究经验的绝佳机会。研究成果将在IEEE/ACM期刊和国际会议上发表。