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.

对无线频谱的需求预计将在未来继续增长，并且只会加剧目前感受到的频谱紧缩。严格的许可政策给予承租人独家和永久使用无线频谱的权利，进一步加剧了这种稀缺性。这个缺点已经在著名的2002年FCC研究中被识别，该研究估计根据时间和位置，许可频谱的利用率在15-85%之间，因此，强调了对频谱共享的新方法的迫切需要。由于用户业务需求、频谱可用性、无线信道条件和用户位置的固有不确定性，这些新方法的开发（被称为动态频谱接入（DSA）技术）非常具有挑战性。因此，该项目的首要目标是在存在这些不确定性的情况下有效地管理动态频谱接入。该项目中开发的算法最终鼓励联邦和商业频谱持有者参与DSA系统。额外的无线带宽正在被释放出来，用于将基本服务迁移到无线领域，从而大大降低了目前被排除在这一市场之外的社会中很大一部分人接入无线网络的成本。动态频谱接入管理面临三大挑战：（1）从二级供应商/用户的角度来看，频谱资源的动态性和可能的相关性;（2）频谱可用性的长期信道统计和实时信道状态的不确定性;（3）频谱资源的动态性和相关性。（3）次级业务的不确定性和次级用户的异构性能/定价要求。在这个项目中，有效的信息共享，频谱感知和调度策略的设计，考虑到所有这三个方面。由于联合优化上述三个方面是一个艰巨的挑战，该项目是在两个相互关联的推力组织。在第一个推力，一个给定的频谱不确定性水平的假设，和有效的调度策略设计的二级供应商，以满足各种QoS要求。在第二个推力，二级供应商可以控制信息不准确的情况下，通过协调SU感测信道被认为是联合感测和调度问题的调查。所开发的算法通过仿真和测试平台的实现进行验证。不确定性的影响进行了研究，通过开发分析技术，结合联合收割机随机优化，近似算法和博弈论。由此产生的联合传感和资源分配策略是低复杂度和可证明有效的。该项目将吸引代表性不足的学生和K-12学生。