NSF-IITP: AI/ML-Enabled Scalable and Privacy-Preserving 6G Space-Air-Ground Integrated Network Operation

NSF-IITP：支持 AI/ML 的可扩展且保护隐私的 6G 天地一体化网络运营

• 批准号: 2242412
• 负责人: Seung-Jun Kim
• 金额: $ 30万
• 依托单位: University of Maryland Baltimore County
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2242412&HistoricalAwards=false
• 关键词: NSF; IITP; AI; ML; Enabled

The 6th generation (6G) wireless technology is envisaged to provide hyperconnectivity across humans, machines, and sensors, fueling the growth of exciting new applications in expanded reality (XR), artificial intelligence (AI), and autonomous robotics, to name a few. This project focuses on the key enabling technology, namely, the integrated non-terrestrial networks (NTNs), which encompass space, air, and ground components, such as the low Earth orbit (LEO) satellites, high-altitude platform stations (HAPSs), and unmanned aerial vehicles (UAVs), in addition to the traditional terrestrial stations. Freeing itself from fixed locations, the space-air-ground integrated network can support seamless connectivity to remote regions (e.g. for climate monitoring), disaster areas, hot spots, and coverage holes, as well as high-mobility clusters such as aircrafts and vessels. Significant technical challenges emerge, however, with such a flexible network architecture. This project aspires to explore novel solutions to critical operational issues of NTNs, by tapping into powerful AI and machine learning (ML) techniques. Notably, the proposed research is designed to benefit from close collaboration among the participating US and South Korean institutions. The research outcomes will substantially advance the theory and practice of 6G integrated networking, secure global technological leadership of the US/Korean workforce, and contribute to societal and environmental agenda by providing vital infrastructure to combat the critical issues therein. The gained knowledge will have impact to other science and technology domains as well, such as network science, data science, distributed robotics, and privacy-preserving smart health. The attendant educational components will provide fresh learning experiences suitable for preparing STEM talents in the US and South Korea.More specifically, the project aims at addressing key challenges associated with NTN operation, ranging from radio environment analysis, space-air-ground integrated routing, multi-satellite coordination, service-aware resource allocation, to privacy protection. While recent advances in AI/ML is expected to be the opportune enabler for this endeavor, it is observed that to ensure efficiency and robustness in the training and operation of the AI/ML modules, traditional data-driven black box approaches need to be complemented with proven domain-specific paradigms and novel ML architectural insights. In this context, diverse expertise in ML, signal processing, communication, networking, and information theory will be pooled together through tight international collaboration to make transformative contributions. Important research agenda to be explored include: 1) Complex radio environment cartography through joint ML and signal processing; 2) scalable network optimization via constrained multi-agent reinforcement learning; and 3) fundamental trade-offs in privacy-preserving inference over wireless networks. Furthermore, integrative research of these agenda will be pursued to devise map-assisted network control methods for highly dynamic NTN scenarios and privacy-preserving map inference and multi-agent coordination schemes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

设想第六代（6G）无线技术可提供人，机器和传感器之间的超连续性，从而助长了扩展现实（XR），人工智能（AI）和自动驾驶机器人技术中令人兴奋的新应用的增长，仅举几例。该项目侧重于关键的启用技术，即综合的非事物网络（NTNS），该技术包括空间，空气和地面组件，例如低地轨道（LEO）卫星，高空平台站（HAPS），以及无人驾驶汽车（无人驾驶汽车（UAVS）），以及传统的terresties terrestials satersials。空间空气地面集成网络从固定位置释放自身可以支持与远程区域的无缝连通性（例如，用于气候监测），灾害区域，热点和覆盖孔以及高弹性群集，例如飞机和船只。但是，具有如此灵活的网络体系结构出现了重大的技术挑战。该项目愿意通过利用强大的AI和机器学习（ML）技术来探索NTN的关键操作问题的新颖解决方案。值得注意的是，拟议的研究旨在从参与美国和韩国机构之间的密切合作中受益。研究成果将大大推动6G综合网络，确保美国/韩国劳动力的全球技术领导的理论和实践，并通过提供重要的基础设施来解决其中的关键问题，从而为社会和环境议程做出贡献。获得的知识也将对其他科学和技术领域产生影响，例如网络科学，数据科学，分布式机器人技术和保护隐私的智能健康。随之而来的教育组成部分将提供适合在美国和韩国准备STEM人才的新鲜学习体验。更具体地说，该项目旨在应对与NTN操作相关的关键挑战，包括无线电环境分析，空间空间的集成路由，多 - 卫星协调，服务吸引的资源分配，到隐私保护。尽管预计AI/ML的最新进展有望成为这项工作的适当推动力，但可以观察到，为了确保AI/ML模块的培训和操作的效率和鲁棒性，需要将传统的数据驱动的黑匣子方法与Proken的域名特异性领域特异性典范和新型ML建筑型建筑iNsights相辅相成。在这种情况下，将通过紧密的国际协作来共同努力，在ML，信号处理，沟通，网络和信息理论方面进行多样化的专业知识，以做出变革性的贡献。要探索的重要研究议程包括：1）通过关节ML和信号处理复杂的无线电环境制图； 2）通过受约束的多代理增强学习可扩展的网络优化； 3）对无线网络的隐私推论的基本权衡。此外，将对这些议程进行整合研究，以设计高度动态的NTN场景和隐私保护地图的地图推理和多代理协调方案。该奖项反映了NSF的法规任务，并认为通过基金会的知识优点和广泛的cribitia cribitia cribia cribia cribitia cribia cribia crcritia crigia crigia crigia crcritia crocritia crocritia crocritia crocritia crocritia crocritia crocritia crocritia均值得一提。