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SpecEES: Secure and Fair Spectrum Sharing for Heterogeneous Coexistent Systems

SpecEES：异构共存系统的安全和公平频谱共享

基本信息

批准号：
1731164
负责人：
Loukas Lazos
金额：
$ 60万
依托单位：
University of Arizona
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：
2017-10-01 至 2022-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1731164&HistoricalAwards=false
关键词：
SpecEES Secure Fair Spectrum Sharing

项目摘要

The dramatic growth in demand for wireless services has fueled a severe spectrum shortage, especially in the overcrowded unlicensed bands. The regulatory approach for meeting this galloping demand is to allow the coexistence of competing wireless technologies, cellular, Wi-Fi, radar, TV, emergency communications, and others. This shared spectrum paradigm poses novel challenges for the secure, efficient, and fair resource allocation. Many of these challenges stem from the heterogeneity of the coexisting systems, their scale, and the lack of explicit coordination mechanisms. Whereas some recent efforts have tried to address the coexistence of specific technologies, a comprehensive and general approach to securely and efficiently coordinate spectrum access for heterogeneous systems remains elusive. By facilitating the fair and secure coexistence of heterogeneous wireless systems, this project directly addresses the spectrum scarcity challenge. The outcomes of this project will benefit many industry verticals such as transportation, manufacturing, agriculture, critical national infrastructure, telecommunications, and others. Moreover, the expected results will advance knowledge in a number of scientific fields including security, privacy, and communication theory. Training opportunities for future wireless and security experts are also provided. This project focuses on developing a novel coexistence framework for coordinating, monitoring, evaluating, and adapting spectrum access in a secure, efficient, and privacy-preserving manner. A general coexistence model in which spectrum can be horizontally and/or vertically shared in time, frequency, and space is considered. For this model, new fairness mechanisms that go beyond airtime sharing and account for unfairness due to spatial multiplexing are being investigated. These mechanisms dynamically allocate resources, not only in frequency and time but also spatially, yielding a fairer coexistence. Moreover, unfairness scenarios due to selfishly ignoring the coexistence etiquette are being modeled and assessed. The critical challenge is to detect and mitigate selfish misbehavior at the device and system level without explicit signaling. To overcome this challenge, the project explores implicit physical layer sensing and monitoring mechanisms that infer various operational attributes and safeguard spectrum access. Finally, the interplay between privacy, interference management, and efficiency in vertical spectrum sharing is investigated. The goal here is to protect the location privacy of assets deployed by legacy operators. Adaptive location obfuscation methods are being developed for achieving a desired degree of privacy while maximizing the spectrum efficiency.

无线服务需求的急剧增长导致了严重的频谱短缺，特别是在过度拥挤的无牌频段。满足这种飞速增长的需求的监管方法是允许相互竞争的无线技术共存，包括蜂窝、Wi-Fi、雷达、电视、紧急通信等。这种频谱共享模式对资源的安全、高效、公平分配提出了新的挑战。许多这些挑战源于共存系统的异质性，它们的规模，以及缺乏明确的协调机制。尽管最近的一些努力试图解决特定技术的共存问题，但一个全面和通用的方法来安全有效地协调异构系统的频谱访问仍然难以捉摸。通过促进异构无线系统的公平和安全共存，该项目直接解决了频谱稀缺的挑战。该项目的成果将惠及许多垂直行业，如交通运输、制造业、农业、关键国家基础设施、电信等。此外，预期的结果将推动包括安全，隐私和通信理论在内的许多科学领域的知识。为未来的无线和安全专家提供培训机会。该项目侧重于开发一种新的共存框架，以安全、高效和保护隐私的方式协调、监测、评估和调整频谱接入。考虑了频谱可以在时间、频率和空间上水平和/或垂直共享的一般共存模型。对于这个模型，新的公平机制正在研究中，它超越了广播时间共享，并解释了空间复用造成的不公平。这些机制不仅在频率和时间上，而且在空间上动态分配资源，从而实现更公平的共存。此外，还对由于自私地忽视共存礼仪而导致的不公平情景进行了建模和评估。关键的挑战是在没有显式信号的情况下检测和减轻设备和系统级别的自私不当行为。为了克服这一挑战，该项目探索了隐含的物理层感知和监测机制，以推断各种操作属性并保护频谱访问。最后，研究了垂直频谱共享中隐私、干扰管理和效率之间的相互作用。这里的目标是保护传统运营商部署的资产的位置隐私。正在开发自适应位置混淆方法，以实现所需的隐私程度，同时最大化频谱效率。

项目成果

期刊论文数量（33）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

On the Privacy and Utility Tradeoff in Database-Assisted Dynamic Spectrum Access

DOI：
10.1109/dyspan.2018.8610485
发表时间：
2018-10
期刊：
2018 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)
影响因子：
0
作者：
Ahmed M. Salama;Ming Li;Loukas Lazos;Yong Xiao;M. Krunz
通讯作者：
Ahmed M. Salama;Ming Li;Loukas Lazos;Yong Xiao;M. Krunz

Privacy-Preserving Aggregate Mobility Data Release: An Information-Theoretic Deep Reinforcement Learning Approach