Collaborative Research: CNS Core: Medium: Softwarizing Millimeter-wave Radio Access Networks (RANs) at the Edge

合作研究：CNS 核心：媒介：边缘毫米波无线接入网络 (RAN) 软件化

• 批准号: 2211944
• 负责人: Tingjun Chen
• 金额: $ 50万
• 依托单位: Duke University
• 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=2211944&HistoricalAwards=false
• 关键词: Collaborative; Research; CNS; Core; Medium

Emerging applications in augmented reality, connected autonomous vehicles, and industrial IoT systems impose demanding requirements on next-generation mobile networks that can hardly be met alone with radio resources below 7 GHz. Therefore, 5G and beyond networks have embraced radios operating in millimeter-wave (mmWave) frequency bands, which offer 25 times or more bandwidth worldwide. On the other hand, mmWave radio networks require the dense deployment of infrastructure nodes to achieve desirable coverage, because mmWave radio signals suffer from high propagation loss and are vulnerable to blockage and mobility. Unfortunately, mmWave infrastructure nodes, e.g., gNodeB in 5G, are made of specialized, dedicated hardware and as a result, their dense deployment would incur formidable capital and operational cost. The goal of the proposed project is to reduce the cost of mmWave radio infrastructure nodes by softwarizing their radio access network (RAN) functions and serving them from data centers close to end users, i.e., edge data centers, therefore facilitating network densification. More importantly, it will allow for previously impossible flexibility in network implementation and configuration as well as efficiency in resource allocation across the network and the edge data center. At the societal level, this project will fuel the ongoing revolution of mobile network virtualization and accelerate the development and deployment of next-generation network systems.The key insight toward addressing the challenges associated with softwarizing mmWave RANs at the edge is to exploit the massive data parallelism inside the mmWave baseband and its inherent structures, with programmable hardware in all domains. The project targets the following scientific contributions in three interrelated research thrusts. (i) A low-latency software realization of the mmWave physical layer for commodity server clusters suitable for edge deployment. (ii) Adaptive RAN configuration and in-network compression schemes that cope with the limited fronthaul capacity in practice, without substantially increasing the cost of mmWave infrastructure nodes. (iii) Novel sensing and imaging schemes based on mmWave radio signals intended for communications. These include sensing with a single mmWave infrastructure node and sensing that leverages multiple coordinated mmWave nodes to achieve previously impossible coverage and resolution.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.

增强现实、互联自动驾驶汽车和工业物联网系统等新兴应用对下一代移动网络提出了苛刻的要求，仅靠7 GHz以下的无线电资源很难满足这些要求。因此，5G及以后的网络采用了在毫米波（mmWave）频段运行的无线电，该频段在全球范围内提供25倍或更多的带宽。另一方面，毫米波无线网络需要密集部署基础设施节点才能实现理想的覆盖，因为毫米波无线电信号的传播损耗高，容易受到阻塞和移动性的影响。不幸的是，毫米波基础设施节点，例如5G中的gndeb，是由专门的专用硬件组成的，因此，它们的密集部署将产生巨大的资本和运营成本。拟议项目的目标是通过软件化无线接入网（RAN）功能，并从靠近最终用户的数据中心（即边缘数据中心）为其提供服务，从而降低毫米波无线电基础设施节点的成本，从而促进网络密度。更重要的是，它将允许以前不可能实现的网络实施和配置灵活性，以及跨网络和边缘数据中心的资源分配效率。在社会层面，该项目将推动正在进行的移动网络虚拟化革命，并加速下一代网络系统的开发和部署。解决与边缘毫米波局域网软件化相关的挑战的关键是利用毫米波基带内部的大量数据并行性及其固有结构，并在所有领域使用可编程硬件。该项目的目标是在三个相互关联的研究重点中作出以下科学贡献。(i)适用于边缘部署的商用服务器集群的毫米波物理层的低延迟软件实现。（ii）自适应RAN配置和网内压缩方案，在不大幅增加毫米波基础设施节点成本的情况下，在实践中应对有限的前传容量。（三）以毫米波无线电信号为基础的用于通信的新型传感和成像方案。其中包括使用单个毫米波基础设施节点进行传感，以及利用多个协调的毫米波节点进行传感，以实现以前不可能实现的覆盖和分辨率。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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

Open-access millimeter-wave software-defined radios in the PAWR COSMOS testbed: Design, deployment, and experimentation

PAWR COSMOS 测试台中的开放接入毫米波软件定义无线电：设计、部署和实验

• DOI: 10.1016/j.comnet.2023.109922
• 发表时间: 2023
• 期刊: Computer Networks
• 影响因子: 5.6
• 作者: Chen, Tingjun;Maddala, Prasanthi;Skrimponis, Panagiotis;Kolodziejski, Jakub;Adhikari, Abhishek;Hu, Hang;Gao, Zhihui;Paidimarri, Arun;Valdes-Garcia, Alberto;Lee, Myung
• 通讯作者: Lee, Myung

Transfer Learning-based ROADM EDFA Wavelength Dependent Gain Prediction Using Minimized Data Collection

使用最小化数据收集进行基于迁移学习的 ROADM EDFA 波长相关增益预测

• DOI: 10.1364/ofc.2023.th2a.1
• 发表时间: 2023
• 期刊: IEEE/Optica Optical Fiber Communication Conference (OFC’23
• 作者: Wang, Zehao;Kilper, Dan;Chen, Tingjun
• 通讯作者: Chen, Tingjun

Open EDFA gain spectrum dataset and its applications in data-driven EDFA gain modeling

开放 EDFA 增益谱数据集及其在数据驱动的 EDFA 增益建模中的应用

• DOI: 10.1364/jocn.491901
• 发表时间: 2023
• 期刊: Journal of Optical Communications and Networking
• 影响因子: 5
• 作者: Wang, Zehao;Kilper, Daniel C.;Chen, Tingjun
• 通讯作者: Chen, Tingjun

First field demonstration of automatic WDM optical path provisioning over alien access links for data center exchange

• DOI: 10.1049/icp.2023.2048
• 发表时间: 2023
• 期刊: 49th European Conference on Optical Communications (ECOC 2023)
• 作者: Toru Mano;T. F. D. Lima;Yue-Kai Huang;Zehao Wang;Wataru Ishida;E. Ip;Andrea D’Amico;S. Okamoto;T. Inoue;H. Nishizawa;V. Curri;G. Zussman;D. Kilper;Tingjun Chen;Ting Wang;Koji Asahi;K. Takasugi

Field Trial of Coexistence and Simultaneous Switching of Real-time Fiber Sensing and 400GbE Supporting DCI and 5G Mobile Services

实时光纤传感与支持 DCI 和 5G 移动服务的 400GbE 共存和同时切换的现场试验

• 发表时间: 2023
• 期刊: Proc. IEEE/OPTICA Optical Fiber Communication Conference (OFC’23
• 作者: Huang, Yue-Kai;Wang, Zehao;Ip, Ezra;Qi, Zhenzhou;Zussman, Gil;Kilper, Dan;Asahi, Koji;Kageshima, Hideo;Aono, Yoshiaki;Chen, Tingjun
• 通讯作者: Chen, Tingjun