EARS: Collaborative: Comprehensive Network State Inference for Robust and Policy-Cognizant Spectrum Access

EARS：协作：全面的网络状态推断，实现稳健且政策认知的频谱访问

• 批准号: 1343256
• 负责人: Mary Ann Weitnauer
• 金额: $ 42.5万
• 依托单位: Georgia Tech Applied Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2016-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1343256&HistoricalAwards=false
• 关键词: EARS; Collaborative; Comprehensive; Network; State

Objective: The objective of this project is a compendious cognition infrastructure enabling robust, cross-layer protocol designs under governance policy constraints, so as to maximize the cognitive radio (CR) network performance and end-user satisfaction, notwithstanding the challenges associated with dynamic and opportunistic radio-spectrum access, as well as the incomplete, corrupt and sporadic data reflecting the cost and restrictions in acquiring network state measurements.Intellectual merit: The intellectual merit is to transform state-of-the-art learning tools for comprehensive and resource-aware cognition of the "global" network state (which includes interference, any-to-any link gains, band occupancies, queue lengths, and path delays), jointly with stochastic, state-cognizant optimization of CR networks with policy implications, to pioneer transformative adaptation approaches to routing, medium-access, and physical-layer designs of wireless CR networks endowed with the much needed robustness to state uncertainty.Broader impacts: The broader impacts include tangible implications to mobile ad hoc, smart grid, intelligent transportation networks, as well as medical telemetry, geo-monitoring, and surveillance systems. Advances in the foundations of kernel-based learning, kernel matrix completion, inference on graphs, and sampling-based scenario optimization, will benefit a gamut of research areas including social analytics, bio-informatics, medical imaging, and surveillance using sensor networks. Policy research integrated with technical components will encourage community embracing of novel CR technologies and open up investment and business opportunities yielding greater economic impact.Undergraduate Design Projects and Botball Competition, facilitated by the proposed Cognitive Spectrum Operations Testbed, will also benefit student training with hands-on experience in state-of-the-art learning, wireless systems on mobile robots, and network optimization subjects.

目的：该项目的目标是一个简明的认知基础设施，在治理政策约束下实现强大的跨层协议设计，以便最大限度地提高认知无线电（CR）网络性能和最终用户满意度，尽管存在与动态和机会主义无线电频谱接入相关的挑战，以及不完整的，损坏和零星的数据反映了获取网络状态测量的成本和限制。智力上的优点是将最先进的学习工具转化为对“全球”网络状态的全面和资源感知认知（包括干扰、任意到任意链路增益、频带占用、队列长度和路径延迟），结合具有政策影响的CR网络的随机、状态认知优化，开创路由、介质访问、和物理层设计的无线CR网络赋予了急需的鲁棒性状态不确定性。更广泛的影响：更广泛的影响包括对移动的自组织、智能电网、智能交通网络以及医疗遥测的切实影响，地理监测和监视系统。基于核的学习、核矩阵完成、图上的推理和基于采样的场景优化的基础方面的进展，将使包括社会分析、生物信息学、医学成像和使用传感器网络的监控在内的所有研究领域受益。与技术要素相结合的政策研究将鼓励社区接受新型CR技术，并开辟投资和商业机会，产生更大的经济影响。由拟议的认知频谱运营测试床推动的本科生设计项目和Botball竞赛也将有利于学生培训，让他们在最先进的学习、移动的机器人上的无线系统和网络优化科目方面获得实践经验。