NeTS: Small: Dynamic Spectrum Access under Uncertainty: Theory, Algorithm Development, and Evaluation

NeTS：小型：不确定性下的动态频谱接入：理论、算法开发和评估

• 批准号: 1421576
• 负责人: Ness Shroff
• 金额: $ 49.99万
• 依托单位: Ohio State 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: 2014-10-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1421576&HistoricalAwards=false
• 关键词: NeTS; Small; Dynamic; Spectrum; Access

The demand for wireless spectrum is projected to continue growing well into the future, and will only worsen the currently felt spectrum crunch. Rigid licensing policies that give exclusive and permanent right of use of wireless spectrum to lessees further exacerbate this scarcity. This shortcoming has been identified in the famous 2002 FCC study, which estimates the utilization of licensed spectrum between 15-85% depending on time and location, thus, underscoring the critical need for new methods of spectrum sharing. Development of these new methods, coined as Dynamic Spectrum Access (DSA) techniques, is very challenging due to the inherent uncertainty in user traffic demand, spectrum availability, wireless channel conditions, and user locations. Thus, the overarching goal of this project is to efficiently manage dynamic spectrum access in the presence of these uncertainties. The algorithms developed in this project ultimately encourage both federal and commercial spectrum holders to participate in DSA systems. Additional wireless bandwidth is being freed up for essential services to be migrated to the wireless domain, significantly lowering the cost of access to wireless networks for a significant fraction of the society currently shut out of this market. These emerging systems also create new communication-based business models, develop community resources, and improve public safety.Managing dynamic spectrum access faces three major challenges induced by: (1) the dynamics and the possibly correlated nature of spectrum resource from a secondary provider/user's perspective; (2) uncertainty about spectrum availability in terms of long-term channel statistics and real-time channel states; (3) uncertainty of secondary traffic and heterogeneous performance/pricing requirements of secondary users. In this project, efficient information sharing, spectrum sensing, and scheduling policies are designed that take all these three aspects into account. Since jointly optimizing across the three dimensions outlined above is a daunting challenge, the project is organized across two inter-related thrusts. In the first thrust, a given level of spectrum uncertainty is assumed, and efficient scheduling policies are designed for a secondary provider to meet various QoS requirements. In the second thrust, the case where a secondary provider can control information inaccuracy by coordinating SUs to sense channels is considered and the joint sensing and scheduling problem investigated. The developed algorithms are validated through simulations and via testbed implementations. The effect of uncertainties is investigated by developing analytical techniques that combine stochastic optimization, approximation algorithms and game theory. The resulting joint sensing and resource allocation policies are low-complexity and provably efficient. This project will engage underrepresented students and K-12 students.

预计对无线频谱的需求将在未来继续增长，并且只会使当前的频谱紧缩恶化。严格的许可政策赋予了专有和永久使用无线频谱的权利，从而进一步加剧了这种稀缺性。在著名的2002 FCC研究中已经确定了这一缺点，该研究估计了根据时间和位置在15-85％之间使用的许可光谱，因此强调了对新频谱共享方法的关键需求。由于用户流量需求，频谱可用性，无线通道条件和用户位置的固有不确定性，这些新方法的开发是动态频谱访问（DSA）技术的创造非常具有挑战性的。因此，该项目的总体目标是在存在这些不确定性的情况下有效管理动态频谱访问。该项目中开发的算法最终鼓励联邦和商业频谱持有人参与DSA系统。额外的无线带宽已被释放，以迁移到无线领域的基本服务，从而大大降低了访问无线网络的成本，因为目前关闭的社会很大一部分社会都被关闭了。这些新兴系统还创建了新的基于通信的业务模型，开发社区资源并改善公共安全。管理动态频谱访问面临的三个主要挑战是：（1）从次级提供商/用户的角度来看，频谱资源的动态和可能相关的性质； （2）关于长期渠道统计和实时渠道状态的频谱可用性的不确定性； （3）次级用户的次级流量和异质性能/定价要求的不确定性。在这个项目中，设计了有效的信息共享，频谱感应和调度策略，可以考虑所有这三个方面。由于在上面概述的三个维度上共同优化是一个艰巨的挑战，因此该项目是在两个相互关联的推力上组织的。在第一个推力中，假定给定的频谱不确定性，并且有效的调度策略旨在为次级提供商满足各种QoS要求。在第二个推力中，辅助提供商可以通过将SUS协调为Sense渠道来控制信息不准确的情况，并研究了关节感应和调度问题。开发的算法通过模拟和测试台实现进行验证。通过开发结合随机优化，近似算法和游戏理论的分析技术来研究不确定性的效果。由此产生的关节感应和资源分配策略是低复杂性的，效率很高。该项目将吸引代表性不足的学生和K-12学生。