Collaborative Research: SWIFT: Decentralized Intelligent Spectrum Sharing in UAV Networks (DISH-uNET) via Hardware-software Co-design

合作研究：SWIFT：通过软硬件协同设计实现无人机网络中的去中心化智能频谱共享 (DISH-uNET)

• 批准号: 2229563
• 负责人: Zhangyu Guan
• 金额: $ 18.95万
• 依托单位: SUNY at Buffalo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2229563&HistoricalAwards=false
• 关键词: Collaborative; Research; SWIFT; Decentralized; Intelligent

Intelligent unmanned aerial vehicles (UAVs, or “drones”) are attracting the interest of the networking community as a “tool” to provide new capabilities, to extend the infrastructure of wireless networks and to make it more flexible and resilient. UAV-aided wireless networks will enable present and future Internet of Things (IoT) and 5G applications and be a driver for new military and civilian applications spanning battlefield inspection, border control and aerial surveillance, precision agriculture, environmental monitoring, transportation and delivery of goods. Currently, despite the great potential of UAV networks, the design of such networks faces great challenges due to the high mobility of UAVs, the limited power constraint of UAVs, and the non-stationary environment. In this project, we will develop novel approaches for decentralized intelligent spectrum sharing in mmWave UAV networks (DISH-uNET). This project will have a significant engineering and societal impact and substantially advance the state-of-the-art in the design of intelligent UAV networks with strong resiliency attributes. The proposed DISH-uNET achieves high efficiency and resilience based on hardware-software co-design through (1) domain-specific energy-efficient systolic accelerators, (2) novel learning-based transceiver design for high mobility UAVs, (3) new decentralized spectrum sharing multiple access control (MAC) for efficient spectrum management and utility optimization, (4) fast adaptation of mobility resilient mmWave beam learning for UAV networks. This project has four main thrusts. (1) Energy-efficient systolic accelerator for simultaneous real-time signal processing and machine learning. (2) Transceiver design for high mobility UAV Communication. (3) Bridging Lyapunov optimization framework, game theory, and reinforcement learning in decentralized spectrum sharing. (4) Mobility-resilient mmWave beam learning. The research team has the unique access to a large-scale UAV testbed, equipped with the state-of-the-art mmWave transceivers. This testbed will be used for extensive evaluations of the proposed DISH-uNET system.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.

智能无人机（UAV，或“无人机”）作为提供新功能、扩展无线网络基础设施并使其更加灵活和有弹性的“工具”，吸引了网络社区的兴趣。无人机辅助无线网络将支持当前和未来的物联网 (IoT) 和 5G 应用，并成为战场检查、边境管制和空中监视、精准农业、环境监测、运输和货物交付等新军事和民用应用的驱动力。目前，尽管无人机网络潜力巨大，但由于无人机的高机动性、有限的功率约束以及非静止环境，无人机网络的设计面临着巨大的挑战。在这个项目中，我们将开发在毫米波无人机网络（DISH-uNET）中实现分散式智能频谱共享的新方法。该项目将产生重大的工程和社会影响，并大幅推进具有强大弹性属性的智能无人机网络设计的最先进水平。所提出的DISH-uNET通过以下方式实现基于硬件-软件协同设计的高效率和弹性：(1)特定领域的节能脉动加速器，(2)用于高移动性无人机的新颖的基于学习的收发器设计，(3)用于高效频谱管理和效用优化的新的分散频谱共享多路访问控制(MAC)，(4)移动弹性毫米波波束学习的快速适应 用于无人机网络。该项目有四个主要目标。 (1) 用于同步实时信号处理和机器学习的节能收缩加速器。 (2)高机动性无人机通信收发机设计。 (3) 在去中心化频谱共享中桥接 Lyapunov 优化框架、博弈论和强化学习。 (4) 移动弹性毫米波波束学习。研究团队拥有使用最先进的毫米波收发器的大型无人机测试台的独特机会。该测试平台将用于对拟议的 DISH-uNET 系统进行广泛评估。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Demo Abstract: Scaling Out srsRAN Through Interfacing Wirelessly srsENB with srsEPC

演示摘要：通过 srsENB 与 srsEPC 无线连接横向扩展 srsRAN

• DOI: 10.1109/infocomwkshps57453.2023.10225836
• 发表时间: 2023
• 期刊: IEEE Conference on Computer Communications
• 作者: Mishra, Neha;Iyengar, Yamini V.;Raikar, Akshay C.;Thomas, Nikitha;Moorthy, Sabarish K.;Hu, Jiangqi;Zhao, Zhiyuan;Mastronarde, Nicholas;Bentley, Elizabeth S.;Medley, Michael
• 通讯作者: Medley, Michael

A Mobility-Resilient Spectrum Sharing Framework for Operating Wireless UAVs in the 6 GHz Band

• DOI: 10.1109/tnet.2023.3274354
• 发表时间: 2023-12
• 期刊: IEEE/ACM Transactions on Networking
• 作者: Jiangqi Hu;Sabarish Krishna Moorthy;Ankush Harindranath;Zhaoxi Zhang;Zhiyuan Zhao;Nicholas Mastronarde;E. Bentley;Scott M. Pudlewski;Zhangyu Guan

NeXT: Architecture, prototyping and measurement of a software-defined testing framework for integrated RF network simulation, experimentation and optimization

NeXT：用于集成射频网络仿真、实验和优化的软件定义测试框架的架构、原型设计和测量

• DOI: 10.1016/j.comcom.2023.08.018
• 发表时间: 2023
• 期刊: Computer Communications
• 影响因子: 6
• 作者: Hu, Jiangqi;Zhao, Zhiyuan;McManus, Maxwell;Moorthy, Sabarish Krishna;Cui, Yuqing;Mastronarde, Nicholas;Bentley, Elizabeth Serena;Medley, Michael;Guan, Zhangyu
• 通讯作者: Guan, Zhangyu

Digital Twin-Enabled Domain Adaptation for Zero-Touch UAV Networks: Survey and Challenges

• DOI: 10.48550/arxiv.2301.03359
• 发表时间: 2022-12
• 期刊: Comput. Networks
• 作者: Maxwell Mcmanus;Yuqing Cui;Josh Zhang;Jiangqi Hu;Sabarish Krishna Moorthy;Zhangyu Guan;Nicholas Mastronarde

Swarm UAV networking with collaborative beamforming and automated ESN learning in the presence of unknown blockages

在存在未知阻塞的情况下，具有协作波束成形和自动 ESN 学习功能的无人机集群网络

• DOI: 10.1016/j.comnet.2023.109804
• 发表时间: 2023
• 期刊: Computer Networks
• 影响因子: 5.6
• 作者: Krishna Moorthy, Sabarish;Mastronarde, Nicholas;Pudlewski, Scott;Bentley, Elizabeth Serena;Guan, Zhangyu
• 通讯作者: Guan, Zhangyu